Abstract

A fully automated method for large-scale segmentation of nerve fibers from coherent anti-Stokes Raman scattering (CARS) microscopy images is presented. The method is specifically designed for CARS images of transverse cross sections of nervous tissue but is also suitable for use with standard light microscopy images. After a detailed description of the two-part segmentation algorithm, its accuracy is quantified by comparing the resulting binary images to manually segmented images. We then demonstrate the ability of our method to retrieve morphological data from CARS images of nerve tissue. Finally, we present the segmentation of a large mosaic of CARS images covering more than half the area of a mouse spinal cord cross section and show evidence of clusters of neurons with similar g-ratios throughout the spinal cord.

© 2014 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
AOTF based molecular hyperspectral imaging system and its applications on nerve morphometry

Qingli Li, Dongrong Xu, Xiaofu He, Yiting Wang, Zenggan Chen, Hongying Liu, Qintong Xu, and Fangmin Guo
Appl. Opt. 52(17) 3891-3901 (2013)

Local assessment of myelin health in a multiple sclerosis mouse model using a 2D Fourier transform approach

Steve Bégin, Erik Bélanger, Sophie Laffray, Benoît Aubé, Émilie Chamma, Jonathan Bélisle, Steve Lacroix, Yves De Koninck, and Daniel Côté
Biomed. Opt. Express 4(10) 2003-2014 (2013)

Ex vivo and in vivo imaging of myelin fibers in mouse brain by coherent anti-Stokes Raman scattering microscopy

Yan Fu, T. Brandon Huff, Han-Wei Wang, Haifeng Wang, and Ji-Xin Cheng
Opt. Express 16(24) 19396-19409 (2008)

References

  • View by:
  • |
  • |
  • |

  1. W. A. H. Rushton, “A theory of the effects of fibre size in medullated nerve,” J. Physiol. 115, 101–122 (1951).
    [PubMed]
  2. K.-A. Nave, “Myelination and the trophic support of long axons,” Nature Rev. Neurosci. 11, 275–283 (2010).
    [Crossref]
  3. R. F. Dunn, D. P. O’Leary, and W. E. Kumley, “Quantitative analysis of micrographs by computer graphics,” J. Microsc. 105, 205–213 (1975).
    [Crossref] [PubMed]
  4. M. A. Matthews, “An electron microscopic study of the relationship between axon diameter and the initiation of myelin production in the peripheral nervous system,” Anat. Rec. 161, 337–351 (1968).
    [Crossref] [PubMed]
  5. D. P. Ewart, W. M. Kuzon, J. S. Fish, and N. H. McKee, “Nerve fibre morphometry: a comparison of techniques,” J. Neurosci. Meth. 29, 143–150 (1989).
    [Crossref]
  6. R. L. Friede and W. Beuche, “Combined scatter diagrams of sheath thickness and fibre calibre in human sural nerves: changes with age and neuropathy,” J. Neurol. Neurosurg. Psychiatry 48, 749–756 (1985).
    [Crossref] [PubMed]
  7. E. Meijering, “Cell Segmentation: 50 Years Down the Road [Life Sciences],” IEEE Signal Processing Mag. 29, 140–145 (2012).
    [Crossref]
  8. S. Uchida, “Image processing and recognition for biological images,” Dev. Growth. Differ. 55, 523–549 (2013).
    [Crossref] [PubMed]
  9. P. Mezin, C. Tenaud, J. L. Bosson, and P. Stoebner, “Morphometric analysis of the peripheral nerve: advantages of the semi-automated interactive method,” J. Neurosci. Meth. 51, 163–169 (1994).
    [Crossref]
  10. D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
    [Crossref]
  11. H. L. More, J. Chen, E. Gibson, J. M. Donelan, and M. F. Beg, “A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images,” J. Neurosci. Meth. 201, 149–158 (2011).
    [Crossref]
  12. G. K. Frykman, H. G. Rutherford, and I. R. Neilsen, “Automated nerve fiber counting using an array processor in a Multi-Mini Computer System,” J. Med. Syst. 3, 81–94 (1979).
    [Crossref]
  13. T. J. Ellis, D. Rosen, and J. B. Cavanagh, “Automated measurement of peripheral nerve fibres in transverse section,” J. Biomed. Eng. 2, 272–280 (1980).
    [Crossref] [PubMed]
  14. I. R. Zimmerman, J. L. Karnes, P. C. O’Brien, and P. J. Dyck, “Imaging system for nerve and fiber tract morphometry: components, approaches, performance, and results,” J. Neuropath. Exp. Neur. 39, 409–419 (1980).
    [Crossref] [PubMed]
  15. Y. Usson, S. Torch, and R. Saxod, “Morphometry of human nerve biopsies by means of automated cytometry: assessment with reference to ultrastructural analysis,” Anal. Cell. Pathol. 3, 91–102 (1991).
    [PubMed]
  16. E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
    [Crossref]
  17. B. Weyn, M. van Remoortere, R. Nuydens, T. Meert, and G. van de Wouwer, “A multiparametric assay for quantitative nerve regeneration evaluation,” J. Microsc. 219, 95–101 (2005).
    [Crossref] [PubMed]
  18. F. Urso-Baiarda and A. O. Grobbelaar, “Practical nerve morphometry,” J. Neurosci. Meth. 156, 333–341 (2006).
    [Crossref]
  19. E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
    [Crossref] [PubMed]
  20. X. Zhao, Z. Pan, J. Wu, G. Zhou, and Y. Zeng, “Automatic identification and morphometry of optic nerve fibers in electron microscopy images,” Comput. Med. Imag. Grap. 34, 179–184 (2010).
    [Crossref]
  21. M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
    [Crossref] [PubMed]
  22. Y. L. Fok, J. K. Chan, and R. T. Chin, “Automated analysis of nerve-cell images using active contour models,” IEEE Trans. Med. Imag. 15, 353–368 (1996).
    [Crossref]
  23. Y.-Y. Wang, Y.-N. Sun, C.-C. K. Lin, and M.-S. Ju, “Segmentation of nerve fibers using multi-level gradient watershed and fuzzy systems,” Artif. Intell. Med. 54, 189–200 (2012).
    [Crossref] [PubMed]
  24. Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
    [Crossref] [PubMed]
  25. Y. Yang, F. Li, L. Gao, Z. Wang, M. J. Thrall, S. S. Shen, K. K. Wong, and S. T. C. Wong, “Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging,” Biomed. Opt. Express 2, 2160–2174 (2011).
    [Crossref] [PubMed]
  26. L. Gao, H. Zhou, M. J. Thrall, F. Li, Y. Yang, Z. Wang, P. Luo, K. K. Wong, G. S. Palapattu, and S. T. C. Wong, “Label-free high-resolution imaging of prostate glands and cavernous nerves using coherent anti-Stokes Raman scattering microscopy,” Biomed. Opt. Express 2, 915–926 (2011).
    [Crossref] [PubMed]
  27. A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
    [Crossref]
  28. A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
    [Crossref] [PubMed]
  29. A. Medyukhina, T. Meyer, S. Heuke, N. Vogler, B. Dietzek, and J. Popp, “Automated seeding-based nuclei segmentation in nonlinear optical microscopy,” Appl. Opt. 52, 6979–6994 (2013).
    [Crossref] [PubMed]
  30. A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82, 4142–4145 (1999).
    [Crossref]
  31. C. L. Evans and X. S. Xie, “Coherent anti-stokes Raman scattering microscopy: chemical imaging for biology and medicine,” Annu. Rev. Anal. Chem. 1, 883–909 (2008).
    [Crossref]
  32. S. Bégin, E. Bélanger, S. Laffray, R. Vallée, and D. C. Côté, “In vivo optical monitoring of tissue pathologies and diseases with vibrational contrast,” J. Biophotonics 2, 632–642 (2009).
    [Crossref] [PubMed]
  33. H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent Anti-Stokes Raman Scattering Imaging of Axonal Myelin in Live Spinal Tissues,” Biophys. J. 89, 581–591 (2005).
    [Crossref] [PubMed]
  34. A. P. Kennedy, J. Sutcliffe, and J.-X. Cheng, “Molecular composition and orientation in myelin figures characterized by coherent anti-stokes Raman scattering microscopy,” Langmuir 21, 6478–6486 (2005).
    [Crossref] [PubMed]
  35. Y. Fu and J.-X. Cheng, “Imaging of Myelin by Coherent Anti-Stokes Raman Scattering Microscopy,” in Animal Models of Acute Neurological Injuries II, (Humana Press, 2012), pp. 281–291.
    [Crossref]
  36. R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
    [Crossref] [PubMed]
  37. Y. Fu, H. Wang, T. B. Huff, R. Shi, and J.-X. Cheng, “Coherent anti-Stokes Raman scattering imaging of myelin degradation reveals a calcium-dependent pathway in lyso-PtdCho-induced demyelination,” J. Neurosci. Res. 85, 2870–2881 (2007).
    [Crossref] [PubMed]
  38. J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
    [Crossref] [PubMed]
  39. Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
    [Crossref] [PubMed]
  40. Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
    [Crossref] [PubMed]
  41. C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
    [Crossref] [PubMed]
  42. E. Bélanger, S. Bégin, S. Laffray, Y. de Koninck, R. Vallée, and D. C. Côté, “Quantitative myelin imaging with coherent anti-Stokes Raman scattering microscopy: alleviating the excitation polarization dependence with circularly polarized laser beams,” Opt. Express 17, 18419–18432 (2009).
    [Crossref]
  43. E. Bélanger, F. P. Henry, R. Vallée, M. A. Randolph, I. E. Kochevar, J. M. Winograd, C. P. Lin, and D. C. Côté, “In vivo evaluation of demyelination and remyelination in a nerve crush injury model,” Biomed. Opt. Express 2, 2698–2708 (2011).
    [Crossref] [PubMed]
  44. S. Bégin, E. Bélanger, S. Laffray, B. Aubé, E. Chamma, J. Bélisle, S. Lacroix, Y. de Koninck, and D. Côté, “Local assessment of myelin health in a multiple sclerosis mouse model using a 2D Fourier transform approach,” Biomed. Opt. Express 4, 2003–2014 (2013).
    [Crossref] [PubMed]
  45. I. Veilleux, J. A. Spencer, D. P. Biss, D. C. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum Electron. 14, 10–18 (2008).
    [Crossref]
  46. S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics 25, 1463–1465 (2009).
    [Crossref] [PubMed]
  47. K. Zuiderveld, “Contrast limited adaptive histogram equalization,” in Graphics Gems IV, P. S. Heckbert, ed. (Academic Press Professional, Inc., 1994), pp. 474–485.
    [Crossref]
  48. M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” Int. J. Comput. Vision 1, 321–331 (1988).
    [Crossref]
  49. T. F. Chan and L. A. Vese, “Active contours without edges,” Trans. Img. Proc. 10, 266–277 (2001).
    [Crossref]
  50. J. A. Sethian, Level Set Methods & Fast Marching Methods : Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (Cambridge University Press, 1999).
  51. R. T. Whitaker, “A Level-Set Approach to 3D Reconstruction from Range Data,” Int. J. Comput. Vision 29, 203–231 (1998).
    [Crossref]
  52. S. Lankton and A. Tannenbaum, “Localizing region-based active contours,” IEEE Trans. Image Processing 17, 2029–2039 (2008).
    [Crossref]
  53. A. Gasecka, A. Daradich, H. Dehez, M. Piché, and D. Côté, “Resolution and contrast enhancement in coherent anti-Stokes Raman-scattering microscopy,” Opt. Lett. 38, 4510–4513 (2013).
    [Crossref] [PubMed]
  54. R. Chav, T. Cresson, C. Kauffmann, and J. A. de Guise, “Method for fast and accurate segmentation processing from prior shape: application to femoral head segmentation on x-ray images,” in “SPIE Medical Imaging,” vol. 7259 (2009), vol. 7259, pp. 72594Y.
  55. L. Vincent, “Minimal path algorithms for the robust detection of linear features in gray images,” in Proceedings of the Fourth International Symposium on Mathematical Morphology and Its Applications to Image and Signal Processing, (Kluwer Academic Publishers, 1998), ISMM ’98, pp. 331–338.
  56. M. P. Dubuisson and A. K. Jain, “A modified Hausdorff distance for object matching,” in “Proceedings of the 12th IAPR International Conference on Pattern Recognition,”, vol. 1 (1994), vol. 1, pp. 566–568.
  57. L. R. Dice, “Measures of the Amount of Ecologic Association Between Species,” Ecology 26, 297 (1945).
    [Crossref]
  58. M. Ross and W. Pawlina, Histology (Lippincott Williams & Wilkins, 2006).

2013 (5)

2012 (6)

A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
[Crossref] [PubMed]

Y.-Y. Wang, Y.-N. Sun, C.-C. K. Lin, and M.-S. Ju, “Segmentation of nerve fibers using multi-level gradient watershed and fuzzy systems,” Artif. Intell. Med. 54, 189–200 (2012).
[Crossref] [PubMed]

Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
[Crossref] [PubMed]

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

E. Meijering, “Cell Segmentation: 50 Years Down the Road [Life Sciences],” IEEE Signal Processing Mag. 29, 140–145 (2012).
[Crossref]

2011 (7)

H. L. More, J. Chen, E. Gibson, J. M. Donelan, and M. F. Beg, “A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images,” J. Neurosci. Meth. 201, 149–158 (2011).
[Crossref]

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
[Crossref] [PubMed]

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

L. Gao, H. Zhou, M. J. Thrall, F. Li, Y. Yang, Z. Wang, P. Luo, K. K. Wong, G. S. Palapattu, and S. T. C. Wong, “Label-free high-resolution imaging of prostate glands and cavernous nerves using coherent anti-Stokes Raman scattering microscopy,” Biomed. Opt. Express 2, 915–926 (2011).
[Crossref] [PubMed]

Y. Yang, F. Li, L. Gao, Z. Wang, M. J. Thrall, S. S. Shen, K. K. Wong, and S. T. C. Wong, “Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging,” Biomed. Opt. Express 2, 2160–2174 (2011).
[Crossref] [PubMed]

E. Bélanger, F. P. Henry, R. Vallée, M. A. Randolph, I. E. Kochevar, J. M. Winograd, C. P. Lin, and D. C. Côté, “In vivo evaluation of demyelination and remyelination in a nerve crush injury model,” Biomed. Opt. Express 2, 2698–2708 (2011).
[Crossref] [PubMed]

2010 (3)

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

X. Zhao, Z. Pan, J. Wu, G. Zhou, and Y. Zeng, “Automatic identification and morphometry of optic nerve fibers in electron microscopy images,” Comput. Med. Imag. Grap. 34, 179–184 (2010).
[Crossref]

K.-A. Nave, “Myelination and the trophic support of long axons,” Nature Rev. Neurosci. 11, 275–283 (2010).
[Crossref]

2009 (3)

S. Bégin, E. Bélanger, S. Laffray, R. Vallée, and D. C. Côté, “In vivo optical monitoring of tissue pathologies and diseases with vibrational contrast,” J. Biophotonics 2, 632–642 (2009).
[Crossref] [PubMed]

E. Bélanger, S. Bégin, S. Laffray, Y. de Koninck, R. Vallée, and D. C. Côté, “Quantitative myelin imaging with coherent anti-Stokes Raman scattering microscopy: alleviating the excitation polarization dependence with circularly polarized laser beams,” Opt. Express 17, 18419–18432 (2009).
[Crossref]

S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics 25, 1463–1465 (2009).
[Crossref] [PubMed]

2008 (3)

S. Lankton and A. Tannenbaum, “Localizing region-based active contours,” IEEE Trans. Image Processing 17, 2029–2039 (2008).
[Crossref]

I. Veilleux, J. A. Spencer, D. P. Biss, D. C. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum Electron. 14, 10–18 (2008).
[Crossref]

C. L. Evans and X. S. Xie, “Coherent anti-stokes Raman scattering microscopy: chemical imaging for biology and medicine,” Annu. Rev. Anal. Chem. 1, 883–909 (2008).
[Crossref]

2007 (2)

Y. Fu, H. Wang, T. B. Huff, R. Shi, and J.-X. Cheng, “Coherent anti-Stokes Raman scattering imaging of myelin degradation reveals a calcium-dependent pathway in lyso-PtdCho-induced demyelination,” J. Neurosci. Res. 85, 2870–2881 (2007).
[Crossref] [PubMed]

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

2006 (1)

F. Urso-Baiarda and A. O. Grobbelaar, “Practical nerve morphometry,” J. Neurosci. Meth. 156, 333–341 (2006).
[Crossref]

2005 (3)

H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent Anti-Stokes Raman Scattering Imaging of Axonal Myelin in Live Spinal Tissues,” Biophys. J. 89, 581–591 (2005).
[Crossref] [PubMed]

A. P. Kennedy, J. Sutcliffe, and J.-X. Cheng, “Molecular composition and orientation in myelin figures characterized by coherent anti-stokes Raman scattering microscopy,” Langmuir 21, 6478–6486 (2005).
[Crossref] [PubMed]

B. Weyn, M. van Remoortere, R. Nuydens, T. Meert, and G. van de Wouwer, “A multiparametric assay for quantitative nerve regeneration evaluation,” J. Microsc. 219, 95–101 (2005).
[Crossref] [PubMed]

2001 (1)

T. F. Chan and L. A. Vese, “Active contours without edges,” Trans. Img. Proc. 10, 266–277 (2001).
[Crossref]

2000 (1)

E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
[Crossref]

1999 (1)

A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82, 4142–4145 (1999).
[Crossref]

1998 (1)

R. T. Whitaker, “A Level-Set Approach to 3D Reconstruction from Range Data,” Int. J. Comput. Vision 29, 203–231 (1998).
[Crossref]

1996 (1)

Y. L. Fok, J. K. Chan, and R. T. Chin, “Automated analysis of nerve-cell images using active contour models,” IEEE Trans. Med. Imag. 15, 353–368 (1996).
[Crossref]

1994 (1)

P. Mezin, C. Tenaud, J. L. Bosson, and P. Stoebner, “Morphometric analysis of the peripheral nerve: advantages of the semi-automated interactive method,” J. Neurosci. Meth. 51, 163–169 (1994).
[Crossref]

1991 (1)

Y. Usson, S. Torch, and R. Saxod, “Morphometry of human nerve biopsies by means of automated cytometry: assessment with reference to ultrastructural analysis,” Anal. Cell. Pathol. 3, 91–102 (1991).
[PubMed]

1989 (1)

D. P. Ewart, W. M. Kuzon, J. S. Fish, and N. H. McKee, “Nerve fibre morphometry: a comparison of techniques,” J. Neurosci. Meth. 29, 143–150 (1989).
[Crossref]

1988 (1)

M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” Int. J. Comput. Vision 1, 321–331 (1988).
[Crossref]

1985 (1)

R. L. Friede and W. Beuche, “Combined scatter diagrams of sheath thickness and fibre calibre in human sural nerves: changes with age and neuropathy,” J. Neurol. Neurosurg. Psychiatry 48, 749–756 (1985).
[Crossref] [PubMed]

1980 (2)

T. J. Ellis, D. Rosen, and J. B. Cavanagh, “Automated measurement of peripheral nerve fibres in transverse section,” J. Biomed. Eng. 2, 272–280 (1980).
[Crossref] [PubMed]

I. R. Zimmerman, J. L. Karnes, P. C. O’Brien, and P. J. Dyck, “Imaging system for nerve and fiber tract morphometry: components, approaches, performance, and results,” J. Neuropath. Exp. Neur. 39, 409–419 (1980).
[Crossref] [PubMed]

1979 (1)

G. K. Frykman, H. G. Rutherford, and I. R. Neilsen, “Automated nerve fiber counting using an array processor in a Multi-Mini Computer System,” J. Med. Syst. 3, 81–94 (1979).
[Crossref]

1975 (1)

R. F. Dunn, D. P. O’Leary, and W. E. Kumley, “Quantitative analysis of micrographs by computer graphics,” J. Microsc. 105, 205–213 (1975).
[Crossref] [PubMed]

1968 (1)

M. A. Matthews, “An electron microscopic study of the relationship between axon diameter and the initiation of myelin production in the peripheral nervous system,” Anat. Rec. 161, 337–351 (1968).
[Crossref] [PubMed]

1951 (1)

W. A. H. Rushton, “A theory of the effects of fibre size in medullated nerve,” J. Physiol. 115, 101–122 (1951).
[PubMed]

1945 (1)

L. R. Dice, “Measures of the Amount of Ecologic Association Between Species,” Ecology 26, 297 (1945).
[Crossref]

Anderson, J. R.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Aubé, B.

Beg, M. F.

H. L. More, J. Chen, E. Gibson, J. M. Donelan, and M. F. Beg, “A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images,” J. Neurosci. Meth. 201, 149–158 (2011).
[Crossref]

Bégin, S.

Bélanger, E.

Bélisle, J.

Beuche, W.

R. L. Friede and W. Beuche, “Combined scatter diagrams of sheath thickness and fibre calibre in human sural nerves: changes with age and neuropathy,” J. Neurol. Neurosurg. Psychiatry 48, 749–756 (1985).
[Crossref] [PubMed]

Biss, D. P.

I. Veilleux, J. A. Spencer, D. P. Biss, D. C. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum Electron. 14, 10–18 (2008).
[Crossref]

Bosson, J. L.

P. Mezin, C. Tenaud, J. L. Bosson, and P. Stoebner, “Morphometric analysis of the peripheral nerve: advantages of the semi-automated interactive method,” J. Neurosci. Meth. 51, 163–169 (1994).
[Crossref]

Brenner, M. J.

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

Cavanagh, J. B.

T. J. Ellis, D. Rosen, and J. B. Cavanagh, “Automated measurement of peripheral nerve fibres in transverse section,” J. Biomed. Eng. 2, 272–280 (1980).
[Crossref] [PubMed]

Chamma, E.

Chan, J. K.

Y. L. Fok, J. K. Chan, and R. T. Chin, “Automated analysis of nerve-cell images using active contour models,” IEEE Trans. Med. Imag. 15, 353–368 (1996).
[Crossref]

Chan, T. F.

T. F. Chan and L. A. Vese, “Active contours without edges,” Trans. Img. Proc. 10, 266–277 (2001).
[Crossref]

Chav, R.

R. Chav, T. Cresson, C. Kauffmann, and J. A. de Guise, “Method for fast and accurate segmentation processing from prior shape: application to femoral head segmentation on x-ray images,” in “SPIE Medical Imaging,” vol. 7259 (2009), vol. 7259, pp. 72594Y.

Chen, J.

H. L. More, J. Chen, E. Gibson, J. M. Donelan, and M. F. Beg, “A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images,” J. Neurosci. Meth. 201, 149–158 (2011).
[Crossref]

Chen, Z.

Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
[Crossref] [PubMed]

Cheng, J.-X.

Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
[Crossref] [PubMed]

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

Y. Fu, H. Wang, T. B. Huff, R. Shi, and J.-X. Cheng, “Coherent anti-Stokes Raman scattering imaging of myelin degradation reveals a calcium-dependent pathway in lyso-PtdCho-induced demyelination,” J. Neurosci. Res. 85, 2870–2881 (2007).
[Crossref] [PubMed]

A. P. Kennedy, J. Sutcliffe, and J.-X. Cheng, “Molecular composition and orientation in myelin figures characterized by coherent anti-stokes Raman scattering microscopy,” Langmuir 21, 6478–6486 (2005).
[Crossref] [PubMed]

H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent Anti-Stokes Raman Scattering Imaging of Axonal Myelin in Live Spinal Tissues,” Biophys. J. 89, 581–591 (2005).
[Crossref] [PubMed]

Y. Fu and J.-X. Cheng, “Imaging of Myelin by Coherent Anti-Stokes Raman Scattering Microscopy,” in Animal Models of Acute Neurological Injuries II, (Humana Press, 2012), pp. 281–291.
[Crossref]

Chin, R. T.

Y. L. Fok, J. K. Chan, and R. T. Chin, “Automated analysis of nerve-cell images using active contour models,” IEEE Trans. Med. Imag. 15, 353–368 (1996).
[Crossref]

Chitnis, T.

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

Côté, D.

Côté, D. C.

E. Bélanger, F. P. Henry, R. Vallée, M. A. Randolph, I. E. Kochevar, J. M. Winograd, C. P. Lin, and D. C. Côté, “In vivo evaluation of demyelination and remyelination in a nerve crush injury model,” Biomed. Opt. Express 2, 2698–2708 (2011).
[Crossref] [PubMed]

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

S. Bégin, E. Bélanger, S. Laffray, R. Vallée, and D. C. Côté, “In vivo optical monitoring of tissue pathologies and diseases with vibrational contrast,” J. Biophotonics 2, 632–642 (2009).
[Crossref] [PubMed]

E. Bélanger, S. Bégin, S. Laffray, Y. de Koninck, R. Vallée, and D. C. Côté, “Quantitative myelin imaging with coherent anti-Stokes Raman scattering microscopy: alleviating the excitation polarization dependence with circularly polarized laser beams,” Opt. Express 17, 18419–18432 (2009).
[Crossref]

I. Veilleux, J. A. Spencer, D. P. Biss, D. C. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum Electron. 14, 10–18 (2008).
[Crossref]

Cresson, T.

R. Chav, T. Cresson, C. Kauffmann, and J. A. de Guise, “Method for fast and accurate segmentation processing from prior shape: application to femoral head segmentation on x-ray images,” in “SPIE Medical Imaging,” vol. 7259 (2009), vol. 7259, pp. 72594Y.

Cuisenaire, O.

E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
[Crossref]

Daradich, A.

de Guise, J. A.

R. Chav, T. Cresson, C. Kauffmann, and J. A. de Guise, “Method for fast and accurate segmentation processing from prior shape: application to femoral head segmentation on x-ray images,” in “SPIE Medical Imaging,” vol. 7259 (2009), vol. 7259, pp. 72594Y.

De Jager, P. L.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

de Koninck, Y.

Dehez, H.

Delbeke, J.

E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
[Crossref]

Denef, J. F.

E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
[Crossref]

Dice, L. R.

L. R. Dice, “Measures of the Amount of Ecologic Association Between Species,” Ecology 26, 297 (1945).
[Crossref]

Dietzek, B.

A. Medyukhina, T. Meyer, S. Heuke, N. Vogler, B. Dietzek, and J. Popp, “Automated seeding-based nuclei segmentation in nonlinear optical microscopy,” Appl. Opt. 52, 6979–6994 (2013).
[Crossref] [PubMed]

A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
[Crossref] [PubMed]

Donelan, J. M.

H. L. More, J. Chen, E. Gibson, J. M. Donelan, and M. F. Beg, “A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images,” J. Neurosci. Meth. 201, 149–158 (2011).
[Crossref]

Dubuisson, M. P.

M. P. Dubuisson and A. K. Jain, “A modified Hausdorff distance for object matching,” in “Proceedings of the 12th IAPR International Conference on Pattern Recognition,”, vol. 1 (1994), vol. 1, pp. 566–568.

Dunn, R. F.

R. F. Dunn, D. P. O’Leary, and W. E. Kumley, “Quantitative analysis of micrographs by computer graphics,” J. Microsc. 105, 205–213 (1975).
[Crossref] [PubMed]

Dyck, P. J.

I. R. Zimmerman, J. L. Karnes, P. C. O’Brien, and P. J. Dyck, “Imaging system for nerve and fiber tract morphometry: components, approaches, performance, and results,” J. Neuropath. Exp. Neur. 39, 409–419 (1980).
[Crossref] [PubMed]

Ellis, T. J.

T. J. Ellis, D. Rosen, and J. B. Cavanagh, “Automated measurement of peripheral nerve fibres in transverse section,” J. Biomed. Eng. 2, 272–280 (1980).
[Crossref] [PubMed]

Evans, C. L.

C. L. Evans and X. S. Xie, “Coherent anti-stokes Raman scattering microscopy: chemical imaging for biology and medicine,” Annu. Rev. Anal. Chem. 1, 883–909 (2008).
[Crossref]

Ewart, D. P.

D. P. Ewart, W. M. Kuzon, J. S. Fish, and N. H. McKee, “Nerve fibre morphometry: a comparison of techniques,” J. Neurosci. Meth. 29, 143–150 (1989).
[Crossref]

Fish, J. S.

D. P. Ewart, W. M. Kuzon, J. S. Fish, and N. H. McKee, “Nerve fibre morphometry: a comparison of techniques,” J. Neurosci. Meth. 29, 143–150 (1989).
[Crossref]

Fok, Y. L.

Y. L. Fok, J. K. Chan, and R. T. Chin, “Automated analysis of nerve-cell images using active contour models,” IEEE Trans. Med. Imag. 15, 353–368 (1996).
[Crossref]

Frederick, T. J.

Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
[Crossref] [PubMed]

Freiman, T. M.

M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
[Crossref] [PubMed]

Freudiger, C. W.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Friede, R. L.

R. L. Friede and W. Beuche, “Combined scatter diagrams of sheath thickness and fibre calibre in human sural nerves: changes with age and neuropathy,” J. Neurol. Neurosurg. Psychiatry 48, 749–756 (1985).
[Crossref] [PubMed]

Frykman, G. K.

G. K. Frykman, H. G. Rutherford, and I. R. Neilsen, “Automated nerve fiber counting using an array processor in a Multi-Mini Computer System,” J. Med. Syst. 3, 81–94 (1979).
[Crossref]

Fu, Y.

Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
[Crossref] [PubMed]

Y. Fu, H. Wang, T. B. Huff, R. Shi, and J.-X. Cheng, “Coherent anti-Stokes Raman scattering imaging of myelin degradation reveals a calcium-dependent pathway in lyso-PtdCho-induced demyelination,” J. Neurosci. Res. 85, 2870–2881 (2007).
[Crossref] [PubMed]

H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent Anti-Stokes Raman Scattering Imaging of Axonal Myelin in Live Spinal Tissues,” Biophys. J. 89, 581–591 (2005).
[Crossref] [PubMed]

Y. Fu and J.-X. Cheng, “Imaging of Myelin by Coherent Anti-Stokes Raman Scattering Microscopy,” in Animal Models of Acute Neurological Injuries II, (Humana Press, 2012), pp. 281–291.
[Crossref]

Galli, R.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Gao, L.

L. Gao, H. Zhou, M. J. Thrall, F. Li, Y. Yang, Z. Wang, P. Luo, K. K. Wong, G. S. Palapattu, and S. T. C. Wong, “Label-free high-resolution imaging of prostate glands and cavernous nerves using coherent anti-Stokes Raman scattering microscopy,” Biomed. Opt. Express 2, 915–926 (2011).
[Crossref] [PubMed]

Y. Yang, F. Li, L. Gao, Z. Wang, M. J. Thrall, S. S. Shen, K. K. Wong, and S. T. C. Wong, “Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging,” Biomed. Opt. Express 2, 2160–2174 (2011).
[Crossref] [PubMed]

A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
[Crossref]

Gasecka, A.

Geiger, K. D.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Gibson, E.

H. L. More, J. Chen, E. Gibson, J. M. Donelan, and M. F. Beg, “A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images,” J. Neurosci. Meth. 201, 149–158 (2011).
[Crossref]

Gierthmuehlen, M.

M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
[Crossref] [PubMed]

Goings, G. E.

Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
[Crossref] [PubMed]

Grobbelaar, A. O.

F. Urso-Baiarda and A. O. Grobbelaar, “Practical nerve morphometry,” J. Neurosci. Meth. 156, 333–341 (2006).
[Crossref]

Haastert-Talini, K.

M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
[Crossref] [PubMed]

Hammoudi, A. A.

A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
[Crossref]

He, X.

Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
[Crossref] [PubMed]

Henry, F. P.

Heuke, S.

Holtom, G. R.

A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82, 4142–4145 (1999).
[Crossref]

Huff, T. B.

Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
[Crossref] [PubMed]

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

Y. Fu, H. Wang, T. B. Huff, R. Shi, and J.-X. Cheng, “Coherent anti-Stokes Raman scattering imaging of myelin degradation reveals a calcium-dependent pathway in lyso-PtdCho-induced demyelination,” J. Neurosci. Res. 85, 2870–2881 (2007).
[Crossref] [PubMed]

Hunter, D. A.

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

Imitola, J.

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

Jain, A. K.

M. P. Dubuisson and A. K. Jain, “A modified Hausdorff distance for object matching,” in “Proceedings of the 12th IAPR International Conference on Pattern Recognition,”, vol. 1 (1994), vol. 1, pp. 566–568.

Ji, M.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Jones, B. W.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Jorgensen, E. M.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Ju, M.-S.

Y.-Y. Wang, Y.-N. Sun, C.-C. K. Lin, and M.-S. Ju, “Segmentation of nerve fibers using multi-level gradient watershed and fuzzy systems,” Artif. Intell. Med. 54, 189–200 (2012).
[Crossref] [PubMed]

Jurrus, E.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Kaminsky, J.

M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
[Crossref] [PubMed]

Karnes, J. L.

I. R. Zimmerman, J. L. Karnes, P. C. O’Brien, and P. J. Dyck, “Imaging system for nerve and fiber tract morphometry: components, approaches, performance, and results,” J. Neuropath. Exp. Neur. 39, 409–419 (1980).
[Crossref] [PubMed]

Kass, M.

M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” Int. J. Comput. Vision 1, 321–331 (1988).
[Crossref]

Kauffmann, C.

R. Chav, T. Cresson, C. Kauffmann, and J. A. de Guise, “Method for fast and accurate segmentation processing from prior shape: application to femoral head segmentation on x-ray images,” in “SPIE Medical Imaging,” vol. 7259 (2009), vol. 7259, pp. 72594Y.

Kennedy, A. P.

A. P. Kennedy, J. Sutcliffe, and J.-X. Cheng, “Molecular composition and orientation in myelin figures characterized by coherent anti-stokes Raman scattering microscopy,” Langmuir 21, 6478–6486 (2005).
[Crossref] [PubMed]

Kesari, S.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Khoury, S. J.

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

Kirsch, M.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Koch, E.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Kochevar, I. E.

Kumley, W. E.

R. F. Dunn, D. P. O’Leary, and W. E. Kumley, “Quantitative analysis of micrographs by computer graphics,” J. Microsc. 105, 205–213 (1975).
[Crossref] [PubMed]

Kuzon, W. M.

D. P. Ewart, W. M. Kuzon, J. S. Fish, and N. H. McKee, “Nerve fibre morphometry: a comparison of techniques,” J. Neurosci. Meth. 29, 143–150 (1989).
[Crossref]

Lacroix, S.

Laffray, S.

Lankton, S.

S. Lankton and A. Tannenbaum, “Localizing region-based active contours,” IEEE Trans. Image Processing 17, 2029–2039 (2008).
[Crossref]

Li, F.

Y. Yang, F. Li, L. Gao, Z. Wang, M. J. Thrall, S. S. Shen, K. K. Wong, and S. T. C. Wong, “Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging,” Biomed. Opt. Express 2, 2160–2174 (2011).
[Crossref] [PubMed]

L. Gao, H. Zhou, M. J. Thrall, F. Li, Y. Yang, Z. Wang, P. Luo, K. K. Wong, G. S. Palapattu, and S. T. C. Wong, “Label-free high-resolution imaging of prostate glands and cavernous nerves using coherent anti-Stokes Raman scattering microscopy,” Biomed. Opt. Express 2, 915–926 (2011).
[Crossref] [PubMed]

A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
[Crossref]

Li, Q.

Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
[Crossref] [PubMed]

Lin, C. P.

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

E. Bélanger, F. P. Henry, R. Vallée, M. A. Randolph, I. E. Kochevar, J. M. Winograd, C. P. Lin, and D. C. Côté, “In vivo evaluation of demyelination and remyelination in a nerve crush injury model,” Biomed. Opt. Express 2, 2698–2708 (2011).
[Crossref] [PubMed]

I. Veilleux, J. A. Spencer, D. P. Biss, D. C. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum Electron. 14, 10–18 (2008).
[Crossref]

Lin, C.-C. K.

Y.-Y. Wang, Y.-N. Sun, C.-C. K. Lin, and M.-S. Ju, “Segmentation of nerve fibers using multi-level gradient watershed and fuzzy systems,” Artif. Intell. Med. 54, 189–200 (2012).
[Crossref] [PubMed]

Liu, H.

Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
[Crossref] [PubMed]

Liu, Y.

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

Luo, P.

Mackinnon, S. E.

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

Macq, B.

E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
[Crossref]

Marc, R. E.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Massoud, Y.

A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
[Crossref]

Matthews, M. A.

M. A. Matthews, “An electron microscopic study of the relationship between axon diameter and the initiation of myelin production in the peripheral nervous system,” Anat. Rec. 161, 337–351 (1968).
[Crossref] [PubMed]

McKee, N. H.

D. P. Ewart, W. M. Kuzon, J. S. Fish, and N. H. McKee, “Nerve fibre morphometry: a comparison of techniques,” J. Neurosci. Meth. 29, 143–150 (1989).
[Crossref]

Medyukhina, A.

A. Medyukhina, T. Meyer, S. Heuke, N. Vogler, B. Dietzek, and J. Popp, “Automated seeding-based nuclei segmentation in nonlinear optical microscopy,” Appl. Opt. 52, 6979–6994 (2013).
[Crossref] [PubMed]

A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
[Crossref] [PubMed]

Meert, T.

B. Weyn, M. van Remoortere, R. Nuydens, T. Meert, and G. van de Wouwer, “A multiparametric assay for quantitative nerve regeneration evaluation,” J. Microsc. 219, 95–101 (2005).
[Crossref] [PubMed]

Meijering, E.

E. Meijering, “Cell Segmentation: 50 Years Down the Road [Life Sciences],” IEEE Signal Processing Mag. 29, 140–145 (2012).
[Crossref]

Meyer, T.

A. Medyukhina, T. Meyer, S. Heuke, N. Vogler, B. Dietzek, and J. Popp, “Automated seeding-based nuclei segmentation in nonlinear optical microscopy,” Appl. Opt. 52, 6979–6994 (2013).
[Crossref] [PubMed]

A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
[Crossref] [PubMed]

Mezin, P.

P. Mezin, C. Tenaud, J. L. Bosson, and P. Stoebner, “Morphometric analysis of the peripheral nerve: advantages of the semi-automated interactive method,” J. Neurosci. Meth. 51, 163–169 (1994).
[Crossref]

Miller, S. D.

Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
[Crossref] [PubMed]

Moradzadeh, A.

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

More, H. L.

H. L. More, J. Chen, E. Gibson, J. M. Donelan, and M. F. Beg, “A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images,” J. Neurosci. Meth. 201, 149–158 (2011).
[Crossref]

Mueller, A.

M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
[Crossref] [PubMed]

Myckatyn, T. M.

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

Nave, K.-A.

K.-A. Nave, “Myelination and the trophic support of long axons,” Nature Rev. Neurosci. 11, 275–283 (2010).
[Crossref]

Neilsen, I. R.

G. K. Frykman, H. G. Rutherford, and I. R. Neilsen, “Automated nerve fiber counting using an array processor in a Multi-Mini Computer System,” J. Med. Syst. 3, 81–94 (1979).
[Crossref]

Nuydens, R.

B. Weyn, M. van Remoortere, R. Nuydens, T. Meert, and G. van de Wouwer, “A multiparametric assay for quantitative nerve regeneration evaluation,” J. Microsc. 219, 95–101 (2005).
[Crossref] [PubMed]

O’Brien, P. C.

I. R. Zimmerman, J. L. Karnes, P. C. O’Brien, and P. J. Dyck, “Imaging system for nerve and fiber tract morphometry: components, approaches, performance, and results,” J. Neuropath. Exp. Neur. 39, 409–419 (1980).
[Crossref] [PubMed]

O’Leary, D. P.

R. F. Dunn, D. P. O’Leary, and W. E. Kumley, “Quantitative analysis of micrographs by computer graphics,” J. Microsc. 105, 205–213 (1975).
[Crossref] [PubMed]

Orringer, D. A.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Ottoboni, L.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Paiva, A. R. C.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Palapattu, G. S.

Pan, Z.

X. Zhao, Z. Pan, J. Wu, G. Zhou, and Y. Zeng, “Automatic identification and morphometry of optic nerve fibers in electron microscopy images,” Comput. Med. Imag. Grap. 34, 179–184 (2010).
[Crossref]

Pawlina, W.

M. Ross and W. Pawlina, Histology (Lippincott Williams & Wilkins, 2006).

Pfannl, R.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Philbert, M. A.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Piché, M.

Plachta, D. T. T.

M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
[Crossref] [PubMed]

Popp, J.

A. Medyukhina, T. Meyer, S. Heuke, N. Vogler, B. Dietzek, and J. Popp, “Automated seeding-based nuclei segmentation in nonlinear optical microscopy,” Appl. Opt. 52, 6979–6994 (2013).
[Crossref] [PubMed]

A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
[Crossref] [PubMed]

Preibisch, S.

S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics 25, 1463–1465 (2009).
[Crossref] [PubMed]

Randolph, M. A.

Rasmussen, S.

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

Romeike, B. F. M.

A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
[Crossref] [PubMed]

Romero, E.

E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
[Crossref]

Rosen, D.

T. J. Ellis, D. Rosen, and J. B. Cavanagh, “Automated measurement of peripheral nerve fibres in transverse section,” J. Biomed. Eng. 2, 272–280 (1980).
[Crossref] [PubMed]

Ross, M.

M. Ross and W. Pawlina, Histology (Lippincott Williams & Wilkins, 2006).

Rushton, W. A. H.

W. A. H. Rushton, “A theory of the effects of fibre size in medullated nerve,” J. Physiol. 115, 101–122 (1951).
[PubMed]

Rutherford, H. G.

G. K. Frykman, H. G. Rutherford, and I. R. Neilsen, “Automated nerve fiber counting using an array processor in a Multi-Mini Computer System,” J. Med. Syst. 3, 81–94 (1979).
[Crossref]

Saalfeld, S.

S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics 25, 1463–1465 (2009).
[Crossref] [PubMed]

Saar, B. G.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Sagher, O.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Saxod, R.

Y. Usson, S. Torch, and R. Saxod, “Morphometry of human nerve biopsies by means of automated cytometry: assessment with reference to ultrastructural analysis,” Anal. Cell. Pathol. 3, 91–102 (1991).
[PubMed]

Schackert, G.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Schmitt, M.

A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
[Crossref] [PubMed]

Sethian, J. A.

J. A. Sethian, Level Set Methods & Fast Marching Methods : Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (Cambridge University Press, 1999).

Shen, S. S.

Shi, R.

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

Y. Fu, H. Wang, T. B. Huff, R. Shi, and J.-X. Cheng, “Coherent anti-Stokes Raman scattering imaging of myelin degradation reveals a calcium-dependent pathway in lyso-PtdCho-induced demyelination,” J. Neurosci. Res. 85, 2870–2881 (2007).
[Crossref] [PubMed]

H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent Anti-Stokes Raman Scattering Imaging of Axonal Myelin in Live Spinal Tissues,” Biophys. J. 89, 581–591 (2005).
[Crossref] [PubMed]

Shi, Y.

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

Sidman, R. L.

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

Sims, J. R.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Sitoci-Ficici, K. H.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Spencer, J. A.

I. Veilleux, J. A. Spencer, D. P. Biss, D. C. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum Electron. 14, 10–18 (2008).
[Crossref]

Steiner, G.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Stieglitz, T.

M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
[Crossref] [PubMed]

Stoebner, P.

P. Mezin, C. Tenaud, J. L. Bosson, and P. Stoebner, “Morphometric analysis of the peripheral nerve: advantages of the semi-automated interactive method,” J. Neurosci. Meth. 51, 163–169 (1994).
[Crossref]

Sun, Y.-N.

Y.-Y. Wang, Y.-N. Sun, C.-C. K. Lin, and M.-S. Ju, “Segmentation of nerve fibers using multi-level gradient watershed and fuzzy systems,” Artif. Intell. Med. 54, 189–200 (2012).
[Crossref] [PubMed]

Sutcliffe, J.

A. P. Kennedy, J. Sutcliffe, and J.-X. Cheng, “Molecular composition and orientation in myelin figures characterized by coherent anti-stokes Raman scattering microscopy,” Langmuir 21, 6478–6486 (2005).
[Crossref] [PubMed]

Tannenbaum, A.

S. Lankton and A. Tannenbaum, “Localizing region-based active contours,” IEEE Trans. Image Processing 17, 2029–2039 (2008).
[Crossref]

Tasdizen, T.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Tenaud, C.

P. Mezin, C. Tenaud, J. L. Bosson, and P. Stoebner, “Morphometric analysis of the peripheral nerve: advantages of the semi-automated interactive method,” J. Neurosci. Meth. 51, 163–169 (1994).
[Crossref]

Terzopoulos, D.

M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” Int. J. Comput. Vision 1, 321–331 (1988).
[Crossref]

Thrall, M. J.

Y. Yang, F. Li, L. Gao, Z. Wang, M. J. Thrall, S. S. Shen, K. K. Wong, and S. T. C. Wong, “Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging,” Biomed. Opt. Express 2, 2160–2174 (2011).
[Crossref] [PubMed]

L. Gao, H. Zhou, M. J. Thrall, F. Li, Y. Yang, Z. Wang, P. Luo, K. K. Wong, G. S. Palapattu, and S. T. C. Wong, “Label-free high-resolution imaging of prostate glands and cavernous nerves using coherent anti-Stokes Raman scattering microscopy,” Biomed. Opt. Express 2, 915–926 (2011).
[Crossref] [PubMed]

A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
[Crossref]

Tomancak, P.

S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics 25, 1463–1465 (2009).
[Crossref] [PubMed]

Torch, S.

Y. Usson, S. Torch, and R. Saxod, “Morphometry of human nerve biopsies by means of automated cytometry: assessment with reference to ultrastructural analysis,” Anal. Cell. Pathol. 3, 91–102 (1991).
[PubMed]

Tung, T. H. H.

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

Uchida, S.

S. Uchida, “Image processing and recognition for biological images,” Dev. Growth. Differ. 55, 523–549 (2013).
[Crossref] [PubMed]

Uckermann, O.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Urso-Baiarda, F.

F. Urso-Baiarda and A. O. Grobbelaar, “Practical nerve morphometry,” J. Neurosci. Meth. 156, 333–341 (2006).
[Crossref]

Usson, Y.

Y. Usson, S. Torch, and R. Saxod, “Morphometry of human nerve biopsies by means of automated cytometry: assessment with reference to ultrastructural analysis,” Anal. Cell. Pathol. 3, 91–102 (1991).
[PubMed]

Vallée, R.

van de Wouwer, G.

B. Weyn, M. van Remoortere, R. Nuydens, T. Meert, and G. van de Wouwer, “A multiparametric assay for quantitative nerve regeneration evaluation,” J. Microsc. 219, 95–101 (2005).
[Crossref] [PubMed]

van Remoortere, M.

B. Weyn, M. van Remoortere, R. Nuydens, T. Meert, and G. van de Wouwer, “A multiparametric assay for quantitative nerve regeneration evaluation,” J. Microsc. 219, 95–101 (2005).
[Crossref] [PubMed]

Veilleux, I.

I. Veilleux, J. A. Spencer, D. P. Biss, D. C. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum Electron. 14, 10–18 (2008).
[Crossref]

Veraart, C.

E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
[Crossref]

Vese, L. A.

T. F. Chan and L. A. Vese, “Active contours without edges,” Trans. Img. Proc. 10, 266–277 (2001).
[Crossref]

Vincent, L.

L. Vincent, “Minimal path algorithms for the robust detection of linear features in gray images,” in Proceedings of the Fourth International Symposium on Mathematical Morphology and Its Applications to Image and Signal Processing, (Kluwer Academic Publishers, 1998), ISMM ’98, pp. 331–338.

Vogler, N.

Waeber, C.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Wang, H.

Y. Fu, H. Wang, T. B. Huff, R. Shi, and J.-X. Cheng, “Coherent anti-Stokes Raman scattering imaging of myelin degradation reveals a calcium-dependent pathway in lyso-PtdCho-induced demyelination,” J. Neurosci. Res. 85, 2870–2881 (2007).
[Crossref] [PubMed]

H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent Anti-Stokes Raman Scattering Imaging of Axonal Myelin in Live Spinal Tissues,” Biophys. J. 89, 581–591 (2005).
[Crossref] [PubMed]

Wang, X.

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

Wang, Y.

Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
[Crossref] [PubMed]

Wang, Y.-Y.

Y.-Y. Wang, Y.-N. Sun, C.-C. K. Lin, and M.-S. Ju, “Segmentation of nerve fibers using multi-level gradient watershed and fuzzy systems,” Artif. Intell. Med. 54, 189–200 (2012).
[Crossref] [PubMed]

Wang, Z.

Y. Yang, F. Li, L. Gao, Z. Wang, M. J. Thrall, S. S. Shen, K. K. Wong, and S. T. C. Wong, “Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging,” Biomed. Opt. Express 2, 2160–2174 (2011).
[Crossref] [PubMed]

L. Gao, H. Zhou, M. J. Thrall, F. Li, Y. Yang, Z. Wang, P. Luo, K. K. Wong, G. S. Palapattu, and S. T. C. Wong, “Label-free high-resolution imaging of prostate glands and cavernous nerves using coherent anti-Stokes Raman scattering microscopy,” Biomed. Opt. Express 2, 915–926 (2011).
[Crossref] [PubMed]

A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
[Crossref]

Watanabe, S.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Wei, C. H.

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

Wei, Y.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Weyn, B.

B. Weyn, M. van Remoortere, R. Nuydens, T. Meert, and G. van de Wouwer, “A multiparametric assay for quantitative nerve regeneration evaluation,” J. Microsc. 219, 95–101 (2005).
[Crossref] [PubMed]

Whitaker, R. T.

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

R. T. Whitaker, “A Level-Set Approach to 3D Reconstruction from Range Data,” Int. J. Comput. Vision 29, 203–231 (1998).
[Crossref]

Whitlock, E. L.

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

Winograd, J. M.

Winterhalder, M. J.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Witkin, A.

M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” Int. J. Comput. Vision 1, 321–331 (1988).
[Crossref]

Wong, K. K.

Wong, S. T. C.

Y. Yang, F. Li, L. Gao, Z. Wang, M. J. Thrall, S. S. Shen, K. K. Wong, and S. T. C. Wong, “Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging,” Biomed. Opt. Express 2, 2160–2174 (2011).
[Crossref] [PubMed]

L. Gao, H. Zhou, M. J. Thrall, F. Li, Y. Yang, Z. Wang, P. Luo, K. K. Wong, G. S. Palapattu, and S. T. C. Wong, “Label-free high-resolution imaging of prostate glands and cavernous nerves using coherent anti-Stokes Raman scattering microscopy,” Biomed. Opt. Express 2, 915–926 (2011).
[Crossref] [PubMed]

A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
[Crossref]

Wu, J.

X. Zhao, Z. Pan, J. Wu, G. Zhou, and Y. Zeng, “Automatic identification and morphometry of optic nerve fibers in electron microscopy images,” Comput. Med. Imag. Grap. 34, 179–184 (2010).
[Crossref]

Xie, X. S.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

C. L. Evans and X. S. Xie, “Coherent anti-stokes Raman scattering microscopy: chemical imaging for biology and medicine,” Annu. Rev. Anal. Chem. 1, 883–909 (2008).
[Crossref]

A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82, 4142–4145 (1999).
[Crossref]

Xu, Q.

Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
[Crossref] [PubMed]

Xu, X.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Xu, X.-M.

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

Yang, Y.

Ying, W.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Young, G. S.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Zeng, Q.

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Zeng, Y.

X. Zhao, Z. Pan, J. Wu, G. Zhou, and Y. Zeng, “Automatic identification and morphometry of optic nerve fibers in electron microscopy images,” Comput. Med. Imag. Grap. 34, 179–184 (2010).
[Crossref]

Zhang, D.

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

Zhao, X.

X. Zhao, Z. Pan, J. Wu, G. Zhou, and Y. Zeng, “Automatic identification and morphometry of optic nerve fibers in electron microscopy images,” Comput. Med. Imag. Grap. 34, 179–184 (2010).
[Crossref]

Zhou, G.

X. Zhao, Z. Pan, J. Wu, G. Zhou, and Y. Zeng, “Automatic identification and morphometry of optic nerve fibers in electron microscopy images,” Comput. Med. Imag. Grap. 34, 179–184 (2010).
[Crossref]

Zhou, H.

Zickmund, P.

H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent Anti-Stokes Raman Scattering Imaging of Axonal Myelin in Live Spinal Tissues,” Biophys. J. 89, 581–591 (2005).
[Crossref] [PubMed]

Zimmerman, I. R.

I. R. Zimmerman, J. L. Karnes, P. C. O’Brien, and P. J. Dyck, “Imaging system for nerve and fiber tract morphometry: components, approaches, performance, and results,” J. Neuropath. Exp. Neur. 39, 409–419 (1980).
[Crossref] [PubMed]

Zuiderveld, K.

K. Zuiderveld, “Contrast limited adaptive histogram equalization,” in Graphics Gems IV, P. S. Heckbert, ed. (Academic Press Professional, Inc., 1994), pp. 474–485.
[Crossref]

Zumbusch, A.

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82, 4142–4145 (1999).
[Crossref]

Anal. Cell. Pathol. (1)

Y. Usson, S. Torch, and R. Saxod, “Morphometry of human nerve biopsies by means of automated cytometry: assessment with reference to ultrastructural analysis,” Anal. Cell. Pathol. 3, 91–102 (1991).
[PubMed]

Anal. Chem. (1)

R. Galli, O. Uckermann, M. J. Winterhalder, K. H. Sitoci-Ficici, K. D. Geiger, E. Koch, G. Schackert, A. Zumbusch, G. Steiner, and M. Kirsch, “Vibrational spectroscopic imaging and multiphoton microscopy of spinal cord injury,” Anal. Chem. 84, 8707–8714 (2012).
[Crossref] [PubMed]

Anat. Rec. (1)

M. A. Matthews, “An electron microscopic study of the relationship between axon diameter and the initiation of myelin production in the peripheral nervous system,” Anat. Rec. 161, 337–351 (1968).
[Crossref] [PubMed]

Annu. Rev. Anal. Chem. (1)

C. L. Evans and X. S. Xie, “Coherent anti-stokes Raman scattering microscopy: chemical imaging for biology and medicine,” Annu. Rev. Anal. Chem. 1, 883–909 (2008).
[Crossref]

Appl. Opt. (1)

Artif. Intell. Med. (1)

Y.-Y. Wang, Y.-N. Sun, C.-C. K. Lin, and M.-S. Ju, “Segmentation of nerve fibers using multi-level gradient watershed and fuzzy systems,” Artif. Intell. Med. 54, 189–200 (2012).
[Crossref] [PubMed]

Bioinformatics (1)

S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics 25, 1463–1465 (2009).
[Crossref] [PubMed]

Biomed. Opt. Express (4)

Biophys. J. (1)

H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent Anti-Stokes Raman Scattering Imaging of Axonal Myelin in Live Spinal Tissues,” Biophys. J. 89, 581–591 (2005).
[Crossref] [PubMed]

Comput. Med. Imag. Grap. (1)

X. Zhao, Z. Pan, J. Wu, G. Zhou, and Y. Zeng, “Automatic identification and morphometry of optic nerve fibers in electron microscopy images,” Comput. Med. Imag. Grap. 34, 179–184 (2010).
[Crossref]

Dev. Growth. Differ. (1)

S. Uchida, “Image processing and recognition for biological images,” Dev. Growth. Differ. 55, 523–549 (2013).
[Crossref] [PubMed]

Ecology (1)

L. R. Dice, “Measures of the Amount of Ecologic Association Between Species,” Ecology 26, 297 (1945).
[Crossref]

IEEE J. Sel. Top. Quantum Electron. (1)

I. Veilleux, J. A. Spencer, D. P. Biss, D. C. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum Electron. 14, 10–18 (2008).
[Crossref]

IEEE Signal Processing Mag. (1)

E. Meijering, “Cell Segmentation: 50 Years Down the Road [Life Sciences],” IEEE Signal Processing Mag. 29, 140–145 (2012).
[Crossref]

IEEE Trans. Image Processing (1)

S. Lankton and A. Tannenbaum, “Localizing region-based active contours,” IEEE Trans. Image Processing 17, 2029–2039 (2008).
[Crossref]

IEEE Trans. Med. Imag. (1)

Y. L. Fok, J. K. Chan, and R. T. Chin, “Automated analysis of nerve-cell images using active contour models,” IEEE Trans. Med. Imag. 15, 353–368 (1996).
[Crossref]

Int. J. Comput. Vision (2)

M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” Int. J. Comput. Vision 1, 321–331 (1988).
[Crossref]

R. T. Whitaker, “A Level-Set Approach to 3D Reconstruction from Range Data,” Int. J. Comput. Vision 29, 203–231 (1998).
[Crossref]

J. Biomed. Eng. (1)

T. J. Ellis, D. Rosen, and J. B. Cavanagh, “Automated measurement of peripheral nerve fibres in transverse section,” J. Biomed. Eng. 2, 272–280 (1980).
[Crossref] [PubMed]

J. Biomed. Opt. (3)

J. Imitola, D. C. Côté, S. Rasmussen, X. S. Xie, Y. Liu, T. Chitnis, R. L. Sidman, C. P. Lin, and S. J. Khoury, “Multimodal coherent anti-Stokes Raman scattering microscopy reveals microglia-associated myelin and axonal dysfunction in multiple sclerosis-like lesions in mice,” J. Biomed. Opt. 16, 021109 (2011).
[Crossref] [PubMed]

Y. Fu, T. J. Frederick, T. B. Huff, G. E. Goings, S. D. Miller, and J.-X. Cheng, “Paranodal myelin retraction in relapsing experimental autoimmune encephalomyelitis visualized by coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 16, 106006 (2011).
[Crossref] [PubMed]

Y. Shi, D. Zhang, T. B. Huff, X. Wang, R. Shi, X.-M. Xu, and J.-X. Cheng, “Longitudinal in vivo coherent anti-Stokes Raman scattering imaging of demyelination and remyelination in injured spinal cord,” J. Biomed. Opt. 16, 106012 (2011).
[Crossref] [PubMed]

J. Biophotonics (2)

A. Medyukhina, T. Meyer, M. Schmitt, B. F. M. Romeike, B. Dietzek, and J. Popp, “Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy,” J. Biophotonics 5, 878–888 (2012).
[Crossref] [PubMed]

S. Bégin, E. Bélanger, S. Laffray, R. Vallée, and D. C. Côté, “In vivo optical monitoring of tissue pathologies and diseases with vibrational contrast,” J. Biophotonics 2, 632–642 (2009).
[Crossref] [PubMed]

J. Med. Syst. (1)

G. K. Frykman, H. G. Rutherford, and I. R. Neilsen, “Automated nerve fiber counting using an array processor in a Multi-Mini Computer System,” J. Med. Syst. 3, 81–94 (1979).
[Crossref]

J. Microsc. (2)

R. F. Dunn, D. P. O’Leary, and W. E. Kumley, “Quantitative analysis of micrographs by computer graphics,” J. Microsc. 105, 205–213 (1975).
[Crossref] [PubMed]

B. Weyn, M. van Remoortere, R. Nuydens, T. Meert, and G. van de Wouwer, “A multiparametric assay for quantitative nerve regeneration evaluation,” J. Microsc. 219, 95–101 (2005).
[Crossref] [PubMed]

J. Neurol. Neurosurg. Psychiatry (1)

R. L. Friede and W. Beuche, “Combined scatter diagrams of sheath thickness and fibre calibre in human sural nerves: changes with age and neuropathy,” J. Neurol. Neurosurg. Psychiatry 48, 749–756 (1985).
[Crossref] [PubMed]

J. Neuropath. Exp. Neur. (1)

I. R. Zimmerman, J. L. Karnes, P. C. O’Brien, and P. J. Dyck, “Imaging system for nerve and fiber tract morphometry: components, approaches, performance, and results,” J. Neuropath. Exp. Neur. 39, 409–419 (1980).
[Crossref] [PubMed]

J. Neurosci. Meth. (6)

E. Romero, O. Cuisenaire, J. F. Denef, J. Delbeke, B. Macq, and C. Veraart, “Automatic morphometry of nerve histological sections,” J. Neurosci. Meth. 97, 111–122 (2000).
[Crossref]

P. Mezin, C. Tenaud, J. L. Bosson, and P. Stoebner, “Morphometric analysis of the peripheral nerve: advantages of the semi-automated interactive method,” J. Neurosci. Meth. 51, 163–169 (1994).
[Crossref]

D. A. Hunter, A. Moradzadeh, E. L. Whitlock, M. J. Brenner, T. M. Myckatyn, C. H. Wei, T. H. H. Tung, and S. E. Mackinnon, “Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve,” J. Neurosci. Meth. 166, 116–124 (2007).
[Crossref]

H. L. More, J. Chen, E. Gibson, J. M. Donelan, and M. F. Beg, “A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images,” J. Neurosci. Meth. 201, 149–158 (2011).
[Crossref]

D. P. Ewart, W. M. Kuzon, J. S. Fish, and N. H. McKee, “Nerve fibre morphometry: a comparison of techniques,” J. Neurosci. Meth. 29, 143–150 (1989).
[Crossref]

F. Urso-Baiarda and A. O. Grobbelaar, “Practical nerve morphometry,” J. Neurosci. Meth. 156, 333–341 (2006).
[Crossref]

J. Neurosci. Res. (1)

Y. Fu, H. Wang, T. B. Huff, R. Shi, and J.-X. Cheng, “Coherent anti-Stokes Raman scattering imaging of myelin degradation reveals a calcium-dependent pathway in lyso-PtdCho-induced demyelination,” J. Neurosci. Res. 85, 2870–2881 (2007).
[Crossref] [PubMed]

J. Physiol. (1)

W. A. H. Rushton, “A theory of the effects of fibre size in medullated nerve,” J. Physiol. 115, 101–122 (1951).
[PubMed]

Lab. Invest. (1)

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, Y. Wei, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92, 1492–1502 (2012).
[Crossref] [PubMed]

Langmuir (1)

A. P. Kennedy, J. Sutcliffe, and J.-X. Cheng, “Molecular composition and orientation in myelin figures characterized by coherent anti-stokes Raman scattering microscopy,” Langmuir 21, 6478–6486 (2005).
[Crossref] [PubMed]

Med. Image Anal. (1)

E. Jurrus, A. R. C. Paiva, S. Watanabe, J. R. Anderson, B. W. Jones, R. T. Whitaker, E. M. Jorgensen, R. E. Marc, and T. Tasdizen, “Detection of neuron membranes in electron microscopy images using a serial neural network architecture,” Med. Image Anal. 14, 770–783 (2010).
[Crossref] [PubMed]

Nature Rev. Neurosci. (1)

K.-A. Nave, “Myelination and the trophic support of long axons,” Nature Rev. Neurosci. 11, 275–283 (2010).
[Crossref]

Neurochem. Int. (1)

Q. Li, Z. Chen, X. He, Y. Wang, H. Liu, and Q. Xu, “Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology,” Neurochem. Int. 61, 1375–1384 (2012).
[Crossref] [PubMed]

Opt. Express (1)

Opt. Lett. (1)

Phys. Rev. Lett. (1)

A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82, 4142–4145 (1999).
[Crossref]

PLOS ONE (1)

M. Gierthmuehlen, T. M. Freiman, K. Haastert-Talini, A. Mueller, J. Kaminsky, T. Stieglitz, and D. T. T. Plachta, “Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct,” PLOS ONE 8, e66191 (2013).
[Crossref] [PubMed]

Trans. Img. Proc. (1)

T. F. Chan and L. A. Vese, “Active contours without edges,” Trans. Img. Proc. 10, 266–277 (2001).
[Crossref]

Other (8)

J. A. Sethian, Level Set Methods & Fast Marching Methods : Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (Cambridge University Press, 1999).

K. Zuiderveld, “Contrast limited adaptive histogram equalization,” in Graphics Gems IV, P. S. Heckbert, ed. (Academic Press Professional, Inc., 1994), pp. 474–485.
[Crossref]

R. Chav, T. Cresson, C. Kauffmann, and J. A. de Guise, “Method for fast and accurate segmentation processing from prior shape: application to femoral head segmentation on x-ray images,” in “SPIE Medical Imaging,” vol. 7259 (2009), vol. 7259, pp. 72594Y.

L. Vincent, “Minimal path algorithms for the robust detection of linear features in gray images,” in Proceedings of the Fourth International Symposium on Mathematical Morphology and Its Applications to Image and Signal Processing, (Kluwer Academic Publishers, 1998), ISMM ’98, pp. 331–338.

M. P. Dubuisson and A. K. Jain, “A modified Hausdorff distance for object matching,” in “Proceedings of the 12th IAPR International Conference on Pattern Recognition,”, vol. 1 (1994), vol. 1, pp. 566–568.

M. Ross and W. Pawlina, Histology (Lippincott Williams & Wilkins, 2006).

A. A. Hammoudi, F. Li, L. Gao, Z. Wang, M. J. Thrall, Y. Massoud, and S. T. C. Wong, “Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks,” in “Machine Learning in Medical Imaging,”, vol. 7009 of Lecture Notes in Computer Science, K. Suzuki, F. Wang, D. Shen, and P. Yan, eds. (Springer Berlin Heidelberg, Berlin, Heidelberg, 2011), pp. 317–325.
[Crossref]

Y. Fu and J.-X. Cheng, “Imaging of Myelin by Coherent Anti-Stokes Raman Scattering Microscopy,” in Animal Models of Acute Neurological Injuries II, (Humana Press, 2012), pp. 281–291.
[Crossref]

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (6)

Fig. 1
Fig. 1 Myelin CARS image of a transverse spinal cord section from a healthy mouse split in two to show a raw unprocessed image section (a) and a section preprocessed with contrast-limited adaptive histogram equalization (b). The image is 752 × 500 pixels in size and an average of 30 frames.
Fig. 2
Fig. 2 Flow chart of the two-part algorithm. (Left) Axon segmentation: 1) detection of axon candidates by extented-minima transform, 2) shape refinement with an active contour method and 3) candidate validation based on their shape. This part produces two binary images of the axon candidates and the background. (Right) Myelin segmentation: 1) segmentation of the myelin outer boundary in the straightened subspace images of the axon candidates, 2) candidate validation based on area overlap and 3) separation of touching myelin pairs by watershed technique. The final output is a binary image representing the myelin sheaths.
Fig. 3
Fig. 3 Axon segmentation in a transverse CARS image of mouse spinal cord. (a) Axon detection with extended-minima transform. (b) Segmentation refinement using an active contour method. (c) Object validation separates the axons (green) from the background (red).
Fig. 4
Fig. 4 Myelin segmentation in a transverse CARS image of mouse spinal cord. (a) The space around an axon (green) is probed along 72 radial lines to produce a straightened subspace image. (b) Sobel filter of the straightened subspace image with the myelin boundary (green). In both (a) and (b), the other axons are shown in blue and the background in red. (c) Segmented myelin. (d) The myelin validation stages uses the area overlap (yellow) as a metric to separate false (red) from true (green) candidates. (e) Connected objects are separated in pairs using a (f) marker-controlled watershed algorithm. (g) Final binary image with separated nerve fibers.
Fig. 5
Fig. 5 Section of a CARS image with overlay for the true positive axons (green), the false positive objects (red), false negative axons (yellow), missed axons (blue) and segmented myelin (cyan). Objects smaller than 10 pixels were discarded prior to the initial validation stage.
Fig. 6
Fig. 6 Nerve fiber segmentation in a CARS mosaic from a transverse section of healthy mouse spinal cord. (a) Myelin sheaths are shown as an overlay, color-coded to the value of the g-ratio. (b) Zoomed-in view of the blue region of interest around the anterior median fissure on the ventral side of the spinal cord. The white arrows show examples where the myelin outer diameter is underestimated. Morphometric parameter 2D histograms of (c) the g-ratio versus axon equivalent diameter and (d) axon equivalent diameter versus fiber equivalent diameter.

Tables (1)

Tables Icon

Table 1 The segmentation accuracy was evaluated using a set of eight CARS images and two toluidine blue stained images of transverse spinal cord sections from healthy mice. True positives (TP) and false positives (FP). The sensitivity, or the true positive rate (TPR), is given by the ratio of the number of true positives (TP) over the number of objects in the ground truth. The precision, or positive predictive value (PPV), is given by the ratio of the number of true positives over the number of true positives plus the number of false positives (FP), i.e., the total number of segmented objects.

Equations (3)

Equations on this page are rendered with MathJax. Learn more.

MHD ( 𝔸 , 𝔹 ) = max ( D ( 𝔸 , 𝔹 ) , D ( 𝔹 , 𝔸 ) )
D ( 𝔸 , 𝔹 ) = 1 N a a 𝔸 d ( a , 𝔹 )
QS ( 𝔸 , 𝔹 ) = 2 N ( 𝔸 𝔹 ) N ( 𝔸 ) + N ( 𝔹 )

Metrics