Abstract

White light endoscopy is widely used for diagnostic imaging of the interior of organs and body cavities, but the inability to correlate individual 2D images with 3D organ morphology limits its utility for quantitative or longitudinal studies of disease physiology or cancer surveillance. As a result, most endoscopy videos, which carry enormous data potential, are used only for real-time guidance and are discarded after collection. We present a computational method to reconstruct and visualize a 3D model of organs from an endoscopic video that captures the shape and surface appearance of the organ. A key aspect of our strategy is the use of advanced computer vision techniques and unmodified, clinical-grade endoscopy hardware with few constraints on the image acquisition protocol, which presents a low barrier to clinical translation. We validate the accuracy and robustness of our reconstruction and co-registration method using cystoscopy videos from tissue-mimicking bladder phantoms and show clinical utility during cystoscopy in the operating room for bladder cancer evaluation. As our method can powerfully augment the visual medical record of the appearance of internal organs, it is broadly applicable to endoscopy and represents a significant advance in cancer surveillance opportunities for big-data cancer research.

© 2017 Optical Society of America

Full Article  |  PDF Article
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References

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  1. D. Ai, J. Yang, J. Fan, Y. Zhao, X. Song, J. Shen, L. Shao, and Y. Wang, “Augmented reality based real-time subcutaneous vein imaging system,” Biomed. Opt. Express 7, 2565–2585 (2016).
    [Crossref] [PubMed]
  2. A. J. Das, T. A. Valdez, J. A. Vargas, P. Saksupapchon, P. Rachapudi, Z. Ge, J. C. Estrada, and R. Raskar, “Volume estimation of tonsil phantoms using an oral camera with 3D imaging,” Biomed. Opt. Express 7, 1445–1457 (2016).
    [Crossref] [PubMed]
  3. Y. M. Kim, S.-E. Baek, J. S. Lim, and W. J. Hyung, “Clinical application of image-enhanced minimally invasive robotic surgery for gastric cancer: a prospective observational study,” J. Gastrointest. Surg. 17, 304–312 (2013).
    [Crossref]
  4. J. C. Lindegaard, K. Tanderup, S. K. Nielsen, S. Haack, and J. Gelineck, “MRI-Guided 3D Optimization Significantly Improves DVH Parameters of Pulsed-Dose-Rate Brachytherapy in Locally Advanced Cervical Cancer,” Int. J. Radiat. Oncol. Biol. Phys. 71, 756–764 (2008).
    [Crossref] [PubMed]
  5. G. F. Riley, A. L. Potosky, J. D. Lubitz, and L. G. Kessler, “Medicare payments from diagnosis to death for elderly cancer patients by stage at diagnosis,” Med. Care 33, 828–841 (1995).
    [Crossref] [PubMed]
  6. S. Atasoy, D. Mateus, A. Meining, G.-Z. Yang, and N. Navab, “Endoscopic video manifolds for targeted optical biopsy,” IEEE Trans Med Imag 31, 637–653 (2012).
    [Crossref]
  7. I. Mehmood, M. Sajjad, and S. W. Baik, “Video summarization based tele-endoscopy: a service to efficiently manage visual data generated during wireless capsule endoscopy procedure,” J. Med. Syst. 38, 000109 (2014).
    [Crossref]
  8. A. Behrens, T. Stehle, S. Gross, and T. Aach, “Local and global panoramic imaging for fluorescence bladder endoscopy,” Conf Proc IEEE Eng Med Biol Soc pp. 6990–6993 (2009).
  9. Y. Hernández-Mier, W. C. P. M. Blondel, C. Daul, D. Wolf, and F. Guillemin, “Fast construction of panoramic images for cystoscopic exploration,” Comput. Med. Imag. Grap. 34, 579–592 (2010).
    [Crossref]
  10. R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
    [Crossref] [PubMed]
  11. A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. Image Und. 117, 1468–1481 (2013).
    [Crossref]
  12. T. D. Soper, M. P. Porter, and E. J. Seibel, “Surface mosaics of the bladder reconstructed from endoscopic video for automated surveillance,” IEEE Trans. Biomed. Eng. 59, 1670–1680 (2012).
    [Crossref] [PubMed]
  13. A. Ben-Hamadou, C. Daul, C. Soussen, A. Rekik, and W. Blondel, “A novel 3D surface construction approach: Appliciation to 3D endoscopic data,” Conf Proc IEEE Image Proc pp. 4425–4428 (2010).
  14. J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
    [PubMed]
  15. M. Agenant, H.-J. Noordmans, W. Koomen, and J. L. H. R. Bosch, “Real-time bladder lesion registration and navigation: a phantom study,” PLOS ONE 8, e54348 (2013).
    [Crossref] [PubMed]
  16. T. Bergen and T. M. Wittenberg, “Stitching and Surface Reconstruction from Endoscopic Image Sequences: A Review of Applications and Methods,” IEEE J. Biomed. Heal. informatics 2194, 1–20 (2014).
  17. L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
    [Crossref] [PubMed]
  18. D. Burschka, M. Li, M. Ishii, R. H. Taylor, and G. D. Hager, “Scale-invariant registration of monocular endoscopic images to CT-scans for sinus surgery,” Med. Image Anal. 9, 413–426 (2005).
    [Crossref] [PubMed]
  19. K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
    [Crossref] [PubMed]
  20. O. G. Grasa, E. Bernal, S. Casado, I. Gil, and J. M. M. Montiel, “Visual slam for handheld monocular endoscope,” IEEE Trans. Med. Imaging 33, 135–146 (2014).
    [Crossref]
  21. M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
    [Crossref]
  22. P. Mountney and G.-Z. Yang, “Dynamic view expansion for minimally invasive surgery using simultaneous localization and mapping,” Conf Proc IEEE Eng Med Biol Soc 2009, 1184–1187 (2009).
    [PubMed]
  23. J. Totz, P. Mountney, D. Stoyanov, and G. Z. Yang, “Dense surface reconstruction for enhanced navigation in MIS,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics)  6891, 89–96 (2011).
    [Crossref]
  24. C. Zach and M. Pollefeys, “Practical methods for convex multi-view reconstruction,” Lect Notes Comput Sc 6314, 354–367 (2010).
    [Crossref]
  25. M. Kazhdan, M. Bolitho, and H. Hoppe, “Poisson surface reconstruction,” Symp Geom Process 7, 61–70 (2006).
  26. M. Waechter, N. Moehrle, and M. Goesele, “Let There Be Color! Large-Scale Texturing of 3D Reconstructions,” Proc ECCV pp. 836–850 (2014).
  27. C. Wengert, M. Reeff, P. C. Cattin, and G. Székely, “Fully Automatic Endoscope Calibration for Intraoperative Use,” Bild. Med 8, 419–423 (2006).
  28. J.-Y. Bouguet, “Camera calibration toolbox for matlab,” ( http://www.vision.caltech.edu/bouguetj/calib_doc/ ) (2004).
  29. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University Press, 2003).
  30. N. Yoshimura and M. B. Chancellor, “Physiology and Pharmacology of the Bladder and Urethra,” in Campbell-Walsh Urol., (Elsevier, 2009), chap. 60, pp. 1786–1833, 10 edit ed.
  31. S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58, R37–R61 (2013).
    [Crossref] [PubMed]
  32. D. G. Lowe, “Distinctive Image Features from Scale-Invariant Keypoints,” Int. J. Comput. Vis. 60, 91–110 (2004).
    [Crossref]
  33. M. Fischler and R. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun ACM 24, 381–395 (1981).
    [Crossref]
  34. D. Nistér and H. Stewénius, “Scalable Recognition with a Vocabulary Tree,” Proc IEEE Comput. Vis. Pattern Recognit. 2, 2161–2168 (2006).
  35. B. Triggs and P. McLauchlan, “Bundle adjustment: a modern synthesis,” Vis. Algorithms 1883, 298–372 (2000).
  36. M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
    [Crossref]
  37. H. Strasdat, J. M. M. Montiel, and A. J. Davison, “Real-time monocular SLAM: Why filter?” IEEE Int Conf Robot Autom pp. 2657–2664 (2010).
  38. A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
    [Crossref]
  39. R. Gal, Y. Wexler, E. Ofek, and H. Hoppe, “Seamless montage for texturing models,” Comput. Graph Forum 29, 479–486 (2010).
    [Crossref]
  40. Y. Boykov and V. Kolmogorov, “An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision,” IEEE Trans. Pattern Anal. Mach. Intell. 26, 1124–1137 (2004).
    [Crossref]
  41. D. Pan and M. S. Soloway, “The importance of transurethral resection in managing patients with urothelial cancer in the bladder: Proposal for a transurethral resection of bladder tumor checklist,” Eur. Urol. 61, 1199–1203 (2012).
    [Crossref] [PubMed]
  42. C. Q. Forster and C. Tozzi, “Towards 3D reconstruction of endoscope images using shape from shading,” SIBGRAPI 200090–96 (2000).
  43. R. Zhang, P.-s. Tsai, J. E. Cryer, and M. Shah, “Shape from Shading : A Survey,” Rev. Lit. Arts Am. 21, 1–41 (1999).
  44. K. Kolev, M. Klodt, T. Brox, and D. Cremers, “Continuous global optimization in multiview 3D reconstruction,” Int. J. Comput. Vis. 84, 80–96 (2009).
    [Crossref]

2016 (2)

2014 (3)

I. Mehmood, M. Sajjad, and S. W. Baik, “Video summarization based tele-endoscopy: a service to efficiently manage visual data generated during wireless capsule endoscopy procedure,” J. Med. Syst. 38, 000109 (2014).
[Crossref]

T. Bergen and T. M. Wittenberg, “Stitching and Surface Reconstruction from Endoscopic Image Sequences: A Review of Applications and Methods,” IEEE J. Biomed. Heal. informatics 2194, 1–20 (2014).

O. G. Grasa, E. Bernal, S. Casado, I. Gil, and J. M. M. Montiel, “Visual slam for handheld monocular endoscope,” IEEE Trans. Med. Imaging 33, 135–146 (2014).
[Crossref]

2013 (5)

M. Agenant, H.-J. Noordmans, W. Koomen, and J. L. H. R. Bosch, “Real-time bladder lesion registration and navigation: a phantom study,” PLOS ONE 8, e54348 (2013).
[Crossref] [PubMed]

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. Image Und. 117, 1468–1481 (2013).
[Crossref]

Y. M. Kim, S.-E. Baek, J. S. Lim, and W. J. Hyung, “Clinical application of image-enhanced minimally invasive robotic surgery for gastric cancer: a prospective observational study,” J. Gastrointest. Surg. 17, 304–312 (2013).
[Crossref]

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58, R37–R61 (2013).
[Crossref] [PubMed]

2012 (5)

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

D. Pan and M. S. Soloway, “The importance of transurethral resection in managing patients with urothelial cancer in the bladder: Proposal for a transurethral resection of bladder tumor checklist,” Eur. Urol. 61, 1199–1203 (2012).
[Crossref] [PubMed]

T. D. Soper, M. P. Porter, and E. J. Seibel, “Surface mosaics of the bladder reconstructed from endoscopic video for automated surveillance,” IEEE Trans. Biomed. Eng. 59, 1670–1680 (2012).
[Crossref] [PubMed]

S. Atasoy, D. Mateus, A. Meining, G.-Z. Yang, and N. Navab, “Endoscopic video manifolds for targeted optical biopsy,” IEEE Trans Med Imag 31, 637–653 (2012).
[Crossref]

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

2011 (1)

J. Totz, P. Mountney, D. Stoyanov, and G. Z. Yang, “Dense surface reconstruction for enhanced navigation in MIS,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics)  6891, 89–96 (2011).
[Crossref]

2010 (3)

C. Zach and M. Pollefeys, “Practical methods for convex multi-view reconstruction,” Lect Notes Comput Sc 6314, 354–367 (2010).
[Crossref]

R. Gal, Y. Wexler, E. Ofek, and H. Hoppe, “Seamless montage for texturing models,” Comput. Graph Forum 29, 479–486 (2010).
[Crossref]

Y. Hernández-Mier, W. C. P. M. Blondel, C. Daul, D. Wolf, and F. Guillemin, “Fast construction of panoramic images for cystoscopic exploration,” Comput. Med. Imag. Grap. 34, 579–592 (2010).
[Crossref]

2009 (3)

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

P. Mountney and G.-Z. Yang, “Dynamic view expansion for minimally invasive surgery using simultaneous localization and mapping,” Conf Proc IEEE Eng Med Biol Soc 2009, 1184–1187 (2009).
[PubMed]

K. Kolev, M. Klodt, T. Brox, and D. Cremers, “Continuous global optimization in multiview 3D reconstruction,” Int. J. Comput. Vis. 84, 80–96 (2009).
[Crossref]

2008 (2)

R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
[Crossref] [PubMed]

J. C. Lindegaard, K. Tanderup, S. K. Nielsen, S. Haack, and J. Gelineck, “MRI-Guided 3D Optimization Significantly Improves DVH Parameters of Pulsed-Dose-Rate Brachytherapy in Locally Advanced Cervical Cancer,” Int. J. Radiat. Oncol. Biol. Phys. 71, 756–764 (2008).
[Crossref] [PubMed]

2006 (3)

M. Kazhdan, M. Bolitho, and H. Hoppe, “Poisson surface reconstruction,” Symp Geom Process 7, 61–70 (2006).

C. Wengert, M. Reeff, P. C. Cattin, and G. Székely, “Fully Automatic Endoscope Calibration for Intraoperative Use,” Bild. Med 8, 419–423 (2006).

D. Nistér and H. Stewénius, “Scalable Recognition with a Vocabulary Tree,” Proc IEEE Comput. Vis. Pattern Recognit. 2, 2161–2168 (2006).

2005 (1)

D. Burschka, M. Li, M. Ishii, R. H. Taylor, and G. D. Hager, “Scale-invariant registration of monocular endoscopic images to CT-scans for sinus surgery,” Med. Image Anal. 9, 413–426 (2005).
[Crossref] [PubMed]

2004 (3)

D. G. Lowe, “Distinctive Image Features from Scale-Invariant Keypoints,” Int. J. Comput. Vis. 60, 91–110 (2004).
[Crossref]

M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
[Crossref]

Y. Boykov and V. Kolmogorov, “An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision,” IEEE Trans. Pattern Anal. Mach. Intell. 26, 1124–1137 (2004).
[Crossref]

2002 (1)

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

2000 (2)

C. Q. Forster and C. Tozzi, “Towards 3D reconstruction of endoscope images using shape from shading,” SIBGRAPI 200090–96 (2000).

B. Triggs and P. McLauchlan, “Bundle adjustment: a modern synthesis,” Vis. Algorithms 1883, 298–372 (2000).

1999 (1)

R. Zhang, P.-s. Tsai, J. E. Cryer, and M. Shah, “Shape from Shading : A Survey,” Rev. Lit. Arts Am. 21, 1–41 (1999).

1995 (1)

G. F. Riley, A. L. Potosky, J. D. Lubitz, and L. G. Kessler, “Medicare payments from diagnosis to death for elderly cancer patients by stage at diagnosis,” Med. Care 33, 828–841 (1995).
[Crossref] [PubMed]

1981 (1)

M. Fischler and R. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun ACM 24, 381–395 (1981).
[Crossref]

Aach, T.

A. Behrens, T. Stehle, S. Gross, and T. Aach, “Local and global panoramic imaging for fluorescence bladder endoscopy,” Conf Proc IEEE Eng Med Biol Soc pp. 6990–6993 (2009).

Agenant, M.

M. Agenant, H.-J. Noordmans, W. Koomen, and J. L. H. R. Bosch, “Real-time bladder lesion registration and navigation: a phantom study,” PLOS ONE 8, e54348 (2013).
[Crossref] [PubMed]

Ai, D.

Aldoma, A.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Atasoy, S.

S. Atasoy, D. Mateus, A. Meining, G.-Z. Yang, and N. Navab, “Endoscopic video manifolds for targeted optical biopsy,” IEEE Trans Med Imag 31, 637–653 (2012).
[Crossref]

Baek, S.-E.

Y. M. Kim, S.-E. Baek, J. S. Lim, and W. J. Hyung, “Clinical application of image-enhanced minimally invasive robotic surgery for gastric cancer: a prospective observational study,” J. Gastrointest. Surg. 17, 304–312 (2013).
[Crossref]

Baik, S. W.

I. Mehmood, M. Sajjad, and S. W. Baik, “Video summarization based tele-endoscopy: a service to efficiently manage visual data generated during wireless capsule endoscopy procedure,” J. Med. Syst. 38, 000109 (2014).
[Crossref]

Bartoli, a.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Behrens, A.

A. Behrens, T. Stehle, S. Gross, and T. Aach, “Local and global panoramic imaging for fluorescence bladder endoscopy,” Conf Proc IEEE Eng Med Biol Soc pp. 6990–6993 (2009).

Bello, F.

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Ben-Hamadou, A.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. Image Und. 117, 1468–1481 (2013).
[Crossref]

A. Ben-Hamadou, C. Daul, C. Soussen, A. Rekik, and W. Blondel, “A novel 3D surface construction approach: Appliciation to 3D endoscopic data,” Conf Proc IEEE Image Proc pp. 4425–4428 (2010).

Bergen, T.

T. Bergen and T. M. Wittenberg, “Stitching and Surface Reconstruction from Endoscopic Image Sequences: A Review of Applications and Methods,” IEEE J. Biomed. Heal. informatics 2194, 1–20 (2014).

Bernal, E.

O. G. Grasa, E. Bernal, S. Casado, I. Gil, and J. M. M. Montiel, “Visual slam for handheld monocular endoscope,” IEEE Trans. Med. Imaging 33, 135–146 (2014).
[Crossref]

Blondel, W.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. Image Und. 117, 1468–1481 (2013).
[Crossref]

A. Ben-Hamadou, C. Daul, C. Soussen, A. Rekik, and W. Blondel, “A novel 3D surface construction approach: Appliciation to 3D endoscopic data,” Conf Proc IEEE Image Proc pp. 4425–4428 (2010).

Blondel, W. C. P. M.

Y. Hernández-Mier, W. C. P. M. Blondel, C. Daul, D. Wolf, and F. Guillemin, “Fast construction of panoramic images for cystoscopic exploration,” Comput. Med. Imag. Grap. 34, 579–592 (2010).
[Crossref]

R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
[Crossref] [PubMed]

Bolitho, M.

M. Kazhdan, M. Bolitho, and H. Hoppe, “Poisson surface reconstruction,” Symp Geom Process 7, 61–70 (2006).

Bolles, R.

M. Fischler and R. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun ACM 24, 381–395 (1981).
[Crossref]

Bosch, J. L. H. R.

M. Agenant, H.-J. Noordmans, W. Koomen, and J. L. H. R. Bosch, “Real-time bladder lesion registration and navigation: a phantom study,” PLOS ONE 8, e54348 (2013).
[Crossref] [PubMed]

Boykov, Y.

Y. Boykov and V. Kolmogorov, “An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision,” IEEE Trans. Pattern Anal. Mach. Intell. 26, 1124–1137 (2004).
[Crossref]

Brox, T.

K. Kolev, M. Klodt, T. Brox, and D. Cremers, “Continuous global optimization in multiview 3D reconstruction,” Int. J. Comput. Vis. 84, 80–96 (2009).
[Crossref]

Burschka, D.

D. Burschka, M. Li, M. Ishii, R. H. Taylor, and G. D. Hager, “Scale-invariant registration of monocular endoscopic images to CT-scans for sinus surgery,” Med. Image Anal. 9, 413–426 (2005).
[Crossref] [PubMed]

Casado, S.

O. G. Grasa, E. Bernal, S. Casado, I. Gil, and J. M. M. Montiel, “Visual slam for handheld monocular endoscope,” IEEE Trans. Med. Imaging 33, 135–146 (2014).
[Crossref]

Casula, R.

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Cattin, P. C.

C. Wengert, M. Reeff, P. C. Cattin, and G. Székely, “Fully Automatic Endoscope Calibration for Intraoperative Use,” Bild. Med 8, 419–423 (2006).

Chancellor, M. B.

N. Yoshimura and M. B. Chancellor, “Physiology and Pharmacology of the Bladder and Urethra,” in Campbell-Walsh Urol., (Elsevier, 2009), chap. 60, pp. 1786–1833, 10 edit ed.

Cremers, D.

K. Kolev, M. Klodt, T. Brox, and D. Cremers, “Continuous global optimization in multiview 3D reconstruction,” Int. J. Comput. Vis. 84, 80–96 (2009).
[Crossref]

Criminisi, A.

M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
[Crossref]

Cryer, J. E.

R. Zhang, P.-s. Tsai, J. E. Cryer, and M. Shah, “Shape from Shading : A Survey,” Rev. Lit. Arts Am. 21, 1–41 (1999).

Das, A. J.

Daul, C.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. Image Und. 117, 1468–1481 (2013).
[Crossref]

Y. Hernández-Mier, W. C. P. M. Blondel, C. Daul, D. Wolf, and F. Guillemin, “Fast construction of panoramic images for cystoscopic exploration,” Comput. Med. Imag. Grap. 34, 579–592 (2010).
[Crossref]

R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
[Crossref] [PubMed]

A. Ben-Hamadou, C. Daul, C. Soussen, A. Rekik, and W. Blondel, “A novel 3D surface construction approach: Appliciation to 3D endoscopic data,” Conf Proc IEEE Image Proc pp. 4425–4428 (2010).

Davison, A. J.

H. Strasdat, J. M. M. Montiel, and A. J. Davison, “Real-time monocular SLAM: Why filter?” IEEE Int Conf Robot Autom pp. 2657–2664 (2010).

Deguchi, D.

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

Edwards, P.

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Elhawary, H.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Elson, D.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Engelbrecht, R.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Estrada, J. C.

Fan, J.

Feussner, H.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Figl, M.

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Fischler, M.

M. Fischler and R. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun ACM 24, 381–395 (1981).
[Crossref]

Forster, C. Q.

C. Q. Forster and C. Tozzi, “Towards 3D reconstruction of endoscope images using shape from shading,” SIBGRAPI 200090–96 (2000).

Gal, R.

R. Gal, Y. Wexler, E. Ofek, and H. Hoppe, “Seamless montage for texturing models,” Comput. Graph Forum 29, 479–486 (2010).
[Crossref]

Ge, Z.

Gedikli, S.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Gelineck, J.

J. C. Lindegaard, K. Tanderup, S. K. Nielsen, S. Haack, and J. Gelineck, “MRI-Guided 3D Optimization Significantly Improves DVH Parameters of Pulsed-Dose-Rate Brachytherapy in Locally Advanced Cervical Cancer,” Int. J. Radiat. Oncol. Biol. Phys. 71, 756–764 (2008).
[Crossref] [PubMed]

Gil, I.

O. G. Grasa, E. Bernal, S. Casado, I. Gil, and J. M. M. Montiel, “Visual slam for handheld monocular endoscope,” IEEE Trans. Med. Imaging 33, 135–146 (2014).
[Crossref]

Goesele, M.

M. Waechter, N. Moehrle, and M. Goesele, “Let There Be Color! Large-Scale Texturing of 3D Reconstructions,” Proc ECCV pp. 836–850 (2014).

Grasa, O. G.

O. G. Grasa, E. Bernal, S. Casado, I. Gil, and J. M. M. Montiel, “Visual slam for handheld monocular endoscope,” IEEE Trans. Med. Imaging 33, 135–146 (2014).
[Crossref]

Groch, a.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Gross, S.

A. Behrens, T. Stehle, S. Gross, and T. Aach, “Local and global panoramic imaging for fluorescence bladder endoscopy,” Conf Proc IEEE Eng Med Biol Soc pp. 6990–6993 (2009).

Guillemin, F.

Y. Hernández-Mier, W. C. P. M. Blondel, C. Daul, D. Wolf, and F. Guillemin, “Fast construction of panoramic images for cystoscopic exploration,” Comput. Med. Imag. Grap. 34, 579–592 (2010).
[Crossref]

R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
[Crossref] [PubMed]

Haack, S.

J. C. Lindegaard, K. Tanderup, S. K. Nielsen, S. Haack, and J. Gelineck, “MRI-Guided 3D Optimization Significantly Improves DVH Parameters of Pulsed-Dose-Rate Brachytherapy in Locally Advanced Cervical Cancer,” Int. J. Radiat. Oncol. Biol. Phys. 71, 756–764 (2008).
[Crossref] [PubMed]

Hager, G. D.

D. Burschka, M. Li, M. Ishii, R. H. Taylor, and G. D. Hager, “Scale-invariant registration of monocular endoscopic images to CT-scans for sinus surgery,” Med. Image Anal. 9, 413–426 (2005).
[Crossref] [PubMed]

Hartley, R.

M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
[Crossref]

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University Press, 2003).

Hawkes, D.

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Hernandez-Mier, Y.

R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
[Crossref] [PubMed]

Hernández-Mier, Y.

Y. Hernández-Mier, W. C. P. M. Blondel, C. Daul, D. Wolf, and F. Guillemin, “Fast construction of panoramic images for cystoscopic exploration,” Comput. Med. Imag. Grap. 34, 579–592 (2010).
[Crossref]

Höller, K.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Hoppe, H.

R. Gal, Y. Wexler, E. Ofek, and H. Hoppe, “Seamless montage for texturing models,” Comput. Graph Forum 29, 479–486 (2010).
[Crossref]

M. Kazhdan, M. Bolitho, and H. Hoppe, “Poisson surface reconstruction,” Symp Geom Process 7, 61–70 (2006).

Hornegger, J.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Hu, M.

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Hyung, W. J.

Y. M. Kim, S.-E. Baek, J. S. Lim, and W. J. Hyung, “Clinical application of image-enhanced minimally invasive robotic surgery for gastric cancer: a prospective observational study,” J. Gastrointest. Surg. 17, 304–312 (2013).
[Crossref]

Ishii, M.

D. Burschka, M. Li, M. Ishii, R. H. Taylor, and G. D. Hager, “Scale-invariant registration of monocular endoscopic images to CT-scans for sinus surgery,” Med. Image Anal. 9, 413–426 (2005).
[Crossref] [PubMed]

Jacques, S. L.

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58, R37–R61 (2013).
[Crossref] [PubMed]

Kang, B.

M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
[Crossref]

Kazhdan, M.

M. Kazhdan, M. Bolitho, and H. Hoppe, “Poisson surface reconstruction,” Symp Geom Process 7, 61–70 (2006).

Kessler, L. G.

G. F. Riley, A. L. Potosky, J. D. Lubitz, and L. G. Kessler, “Medicare payments from diagnosis to death for elderly cancer patients by stage at diagnosis,” Med. Care 33, 828–841 (1995).
[Crossref] [PubMed]

Kim, Y. M.

Y. M. Kim, S.-E. Baek, J. S. Lim, and W. J. Hyung, “Clinical application of image-enhanced minimally invasive robotic surgery for gastric cancer: a prospective observational study,” J. Gastrointest. Surg. 17, 304–312 (2013).
[Crossref]

Klodt, M.

K. Kolev, M. Klodt, T. Brox, and D. Cremers, “Continuous global optimization in multiview 3D reconstruction,” Int. J. Comput. Vis. 84, 80–96 (2009).
[Crossref]

Kolb, a.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Kolev, K.

K. Kolev, M. Klodt, T. Brox, and D. Cremers, “Continuous global optimization in multiview 3D reconstruction,” Int. J. Comput. Vis. 84, 80–96 (2009).
[Crossref]

Kolmogorov, V.

Y. Boykov and V. Kolmogorov, “An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision,” IEEE Trans. Pattern Anal. Mach. Intell. 26, 1124–1137 (2004).
[Crossref]

Koomen, W.

M. Agenant, H.-J. Noordmans, W. Koomen, and J. L. H. R. Bosch, “Real-time bladder lesion registration and navigation: a phantom study,” PLOS ONE 8, e54348 (2013).
[Crossref] [PubMed]

Li, M.

D. Burschka, M. Li, M. Ishii, R. H. Taylor, and G. D. Hager, “Scale-invariant registration of monocular endoscopic images to CT-scans for sinus surgery,” Med. Image Anal. 9, 413–426 (2005).
[Crossref] [PubMed]

Lim, J. S.

Y. M. Kim, S.-E. Baek, J. S. Lim, and W. J. Hyung, “Clinical application of image-enhanced minimally invasive robotic surgery for gastric cancer: a prospective observational study,” J. Gastrointest. Surg. 17, 304–312 (2013).
[Crossref]

Lindegaard, J. C.

J. C. Lindegaard, K. Tanderup, S. K. Nielsen, S. Haack, and J. Gelineck, “MRI-Guided 3D Optimization Significantly Improves DVH Parameters of Pulsed-Dose-Rate Brachytherapy in Locally Advanced Cervical Cancer,” Int. J. Radiat. Oncol. Biol. Phys. 71, 756–764 (2008).
[Crossref] [PubMed]

Lowe, D. G.

D. G. Lowe, “Distinctive Image Features from Scale-Invariant Keypoints,” Int. J. Comput. Vis. 60, 91–110 (2004).
[Crossref]

Lubitz, J. D.

G. F. Riley, A. L. Potosky, J. D. Lubitz, and L. G. Kessler, “Medicare payments from diagnosis to death for elderly cancer patients by stage at diagnosis,” Med. Care 33, 828–841 (1995).
[Crossref] [PubMed]

Maier-Hein, L.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Marton, Z. C.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Mateus, D.

S. Atasoy, D. Mateus, A. Meining, G.-Z. Yang, and N. Navab, “Endoscopic video manifolds for targeted optical biopsy,” IEEE Trans Med Imag 31, 637–653 (2012).
[Crossref]

Maurer, C. R.

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

McLauchlan, P.

B. Triggs and P. McLauchlan, “Bundle adjustment: a modern synthesis,” Vis. Algorithms 1883, 298–372 (2000).

Mehmood, I.

I. Mehmood, M. Sajjad, and S. W. Baik, “Video summarization based tele-endoscopy: a service to efficiently manage visual data generated during wireless capsule endoscopy procedure,” J. Med. Syst. 38, 000109 (2014).
[Crossref]

Meining, A.

S. Atasoy, D. Mateus, A. Meining, G.-Z. Yang, and N. Navab, “Endoscopic video manifolds for targeted optical biopsy,” IEEE Trans Med Imag 31, 637–653 (2012).
[Crossref]

Miranda-Luna, R.

R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
[Crossref] [PubMed]

Moehrle, N.

M. Waechter, N. Moehrle, and M. Goesele, “Let There Be Color! Large-Scale Texturing of 3D Reconstructions,” Proc ECCV pp. 836–850 (2014).

Montiel, J. M. M.

O. G. Grasa, E. Bernal, S. Casado, I. Gil, and J. M. M. Montiel, “Visual slam for handheld monocular endoscope,” IEEE Trans. Med. Imaging 33, 135–146 (2014).
[Crossref]

H. Strasdat, J. M. M. Montiel, and A. J. Davison, “Real-time monocular SLAM: Why filter?” IEEE Int Conf Robot Autom pp. 2657–2664 (2010).

Mori, K.

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

Mountney, P.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

J. Totz, P. Mountney, D. Stoyanov, and G. Z. Yang, “Dense surface reconstruction for enhanced navigation in MIS,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics)  6891, 89–96 (2011).
[Crossref]

P. Mountney and G.-Z. Yang, “Dynamic view expansion for minimally invasive surgery using simultaneous localization and mapping,” Conf Proc IEEE Eng Med Biol Soc 2009, 1184–1187 (2009).
[PubMed]

Natori, H.

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

Navab, N.

S. Atasoy, D. Mateus, A. Meining, G.-Z. Yang, and N. Navab, “Endoscopic video manifolds for targeted optical biopsy,” IEEE Trans Med Imag 31, 637–653 (2012).
[Crossref]

Nielsen, S. K.

J. C. Lindegaard, K. Tanderup, S. K. Nielsen, S. Haack, and J. Gelineck, “MRI-Guided 3D Optimization Significantly Improves DVH Parameters of Pulsed-Dose-Rate Brachytherapy in Locally Advanced Cervical Cancer,” Int. J. Radiat. Oncol. Biol. Phys. 71, 756–764 (2008).
[Crossref] [PubMed]

Nistér, D.

D. Nistér and H. Stewénius, “Scalable Recognition with a Vocabulary Tree,” Proc IEEE Comput. Vis. Pattern Recognit. 2, 2161–2168 (2006).

Noordmans, H.-J.

M. Agenant, H.-J. Noordmans, W. Koomen, and J. L. H. R. Bosch, “Real-time bladder lesion registration and navigation: a phantom study,” PLOS ONE 8, e54348 (2013).
[Crossref] [PubMed]

Ofek, E.

R. Gal, Y. Wexler, E. Ofek, and H. Hoppe, “Seamless montage for texturing models,” Comput. Graph Forum 29, 479–486 (2010).
[Crossref]

Pan, D.

D. Pan and M. S. Soloway, “The importance of transurethral resection in managing patients with urothelial cancer in the bladder: Proposal for a transurethral resection of bladder tumor checklist,” Eur. Urol. 61, 1199–1203 (2012).
[Crossref] [PubMed]

Penne, J.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Penney, G.

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Pollefeys, M.

C. Zach and M. Pollefeys, “Practical methods for convex multi-view reconstruction,” Lect Notes Comput Sc 6314, 354–367 (2010).
[Crossref]

Porter, M. P.

T. D. Soper, M. P. Porter, and E. J. Seibel, “Surface mosaics of the bladder reconstructed from endoscopic video for automated surveillance,” IEEE Trans. Biomed. Eng. 59, 1670–1680 (2012).
[Crossref] [PubMed]

Potosky, A. L.

G. F. Riley, A. L. Potosky, J. D. Lubitz, and L. G. Kessler, “Medicare payments from diagnosis to death for elderly cancer patients by stage at diagnosis,” Med. Care 33, 828–841 (1995).
[Crossref] [PubMed]

Potthast, C.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Rachapudi, P.

Raskar, R.

Reeff, M.

C. Wengert, M. Reeff, P. C. Cattin, and G. Székely, “Fully Automatic Endoscope Calibration for Intraoperative Use,” Bild. Med 8, 419–423 (2006).

Rekik, A.

A. Ben-Hamadou, C. Daul, C. Soussen, A. Rekik, and W. Blondel, “A novel 3D surface construction approach: Appliciation to 3D endoscopic data,” Conf Proc IEEE Image Proc pp. 4425–4428 (2010).

Riley, G. F.

G. F. Riley, A. L. Potosky, J. D. Lubitz, and L. G. Kessler, “Medicare payments from diagnosis to death for elderly cancer patients by stage at diagnosis,” Med. Care 33, 828–841 (1995).
[Crossref] [PubMed]

Rodrigues, M.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Rueckert, D.

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Rusu, R.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Sajjad, M.

I. Mehmood, M. Sajjad, and S. W. Baik, “Video summarization based tele-endoscopy: a service to efficiently manage visual data generated during wireless capsule endoscopy procedure,” J. Med. Syst. 38, 000109 (2014).
[Crossref]

Saksupapchon, P.

Schmauss, B.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Schneider, A.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Schrauder, T.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Seibel, E. J.

T. D. Soper, M. P. Porter, and E. J. Seibel, “Surface mosaics of the bladder reconstructed from endoscopic video for automated surveillance,” IEEE Trans. Biomed. Eng. 59, 1670–1680 (2012).
[Crossref] [PubMed]

Shah, M.

R. Zhang, P.-s. Tsai, J. E. Cryer, and M. Shah, “Shape from Shading : A Survey,” Rev. Lit. Arts Am. 21, 1–41 (1999).

Shao, L.

Shen, J.

Soloway, M. S.

D. Pan and M. S. Soloway, “The importance of transurethral resection in managing patients with urothelial cancer in the bladder: Proposal for a transurethral resection of bladder tumor checklist,” Eur. Urol. 61, 1199–1203 (2012).
[Crossref] [PubMed]

Song, X.

Soper, T. D.

T. D. Soper, M. P. Porter, and E. J. Seibel, “Surface mosaics of the bladder reconstructed from endoscopic video for automated surveillance,” IEEE Trans. Biomed. Eng. 59, 1670–1680 (2012).
[Crossref] [PubMed]

Sorger, J.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Soussen, C.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. Image Und. 117, 1468–1481 (2013).
[Crossref]

A. Ben-Hamadou, C. Daul, C. Soussen, A. Rekik, and W. Blondel, “A novel 3D surface construction approach: Appliciation to 3D endoscopic data,” Conf Proc IEEE Image Proc pp. 4425–4428 (2010).

Speidel, S.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

Stehle, T.

A. Behrens, T. Stehle, S. Gross, and T. Aach, “Local and global panoramic imaging for fluorescence bladder endoscopy,” Conf Proc IEEE Eng Med Biol Soc pp. 6990–6993 (2009).

Stewénius, H.

D. Nistér and H. Stewénius, “Scalable Recognition with a Vocabulary Tree,” Proc IEEE Comput. Vis. Pattern Recognit. 2, 2161–2168 (2006).

Stoyanov, D.

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

J. Totz, P. Mountney, D. Stoyanov, and G. Z. Yang, “Dense surface reconstruction for enhanced navigation in MIS,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics)  6891, 89–96 (2011).
[Crossref]

Strasdat, H.

H. Strasdat, J. M. M. Montiel, and A. J. Davison, “Real-time monocular SLAM: Why filter?” IEEE Int Conf Robot Autom pp. 2657–2664 (2010).

Stürmer, M.

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Suenaga, Y.

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

Sugiyama, J.

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

Székely, G.

C. Wengert, M. Reeff, P. C. Cattin, and G. Székely, “Fully Automatic Endoscope Calibration for Intraoperative Use,” Bild. Med 8, 419–423 (2006).

Szeliski, R.

M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
[Crossref]

Takabatake, H.

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

Tanderup, K.

J. C. Lindegaard, K. Tanderup, S. K. Nielsen, S. Haack, and J. Gelineck, “MRI-Guided 3D Optimization Significantly Improves DVH Parameters of Pulsed-Dose-Rate Brachytherapy in Locally Advanced Cervical Cancer,” Int. J. Radiat. Oncol. Biol. Phys. 71, 756–764 (2008).
[Crossref] [PubMed]

Taylor, R. H.

D. Burschka, M. Li, M. Ishii, R. H. Taylor, and G. D. Hager, “Scale-invariant registration of monocular endoscopic images to CT-scans for sinus surgery,” Med. Image Anal. 9, 413–426 (2005).
[Crossref] [PubMed]

Tombari, F.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Toriwaki, J.

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

Totz, J.

J. Totz, P. Mountney, D. Stoyanov, and G. Z. Yang, “Dense surface reconstruction for enhanced navigation in MIS,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics)  6891, 89–96 (2011).
[Crossref]

Tozzi, C.

C. Q. Forster and C. Tozzi, “Towards 3D reconstruction of endoscope images using shape from shading,” SIBGRAPI 200090–96 (2000).

Triggs, B.

B. Triggs and P. McLauchlan, “Bundle adjustment: a modern synthesis,” Vis. Algorithms 1883, 298–372 (2000).

Tsai, P.-s.

R. Zhang, P.-s. Tsai, J. E. Cryer, and M. Shah, “Shape from Shading : A Survey,” Rev. Lit. Arts Am. 21, 1–41 (1999).

Uyttendaele, M.

M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
[Crossref]

Valdez, T. A.

Vargas, J. A.

Vincze, M.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Waechter, M.

M. Waechter, N. Moehrle, and M. Goesele, “Let There Be Color! Large-Scale Texturing of 3D Reconstructions,” Proc ECCV pp. 836–850 (2014).

Wang, Y.

Wengert, C.

C. Wengert, M. Reeff, P. C. Cattin, and G. Székely, “Fully Automatic Endoscope Calibration for Intraoperative Use,” Bild. Med 8, 419–423 (2006).

Wexler, Y.

R. Gal, Y. Wexler, E. Ofek, and H. Hoppe, “Seamless montage for texturing models,” Comput. Graph Forum 29, 479–486 (2010).
[Crossref]

Winder, S.

M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
[Crossref]

Wittenberg, T. M.

T. Bergen and T. M. Wittenberg, “Stitching and Surface Reconstruction from Endoscopic Image Sequences: A Review of Applications and Methods,” IEEE J. Biomed. Heal. informatics 2194, 1–20 (2014).

Wohlkinger, W.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Wolf, D.

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. Image Und. 117, 1468–1481 (2013).
[Crossref]

Y. Hernández-Mier, W. C. P. M. Blondel, C. Daul, D. Wolf, and F. Guillemin, “Fast construction of panoramic images for cystoscopic exploration,” Comput. Med. Imag. Grap. 34, 579–592 (2010).
[Crossref]

R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
[Crossref] [PubMed]

Yang, G. Z.

J. Totz, P. Mountney, D. Stoyanov, and G. Z. Yang, “Dense surface reconstruction for enhanced navigation in MIS,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics)  6891, 89–96 (2011).
[Crossref]

Yang, G.-Z.

S. Atasoy, D. Mateus, A. Meining, G.-Z. Yang, and N. Navab, “Endoscopic video manifolds for targeted optical biopsy,” IEEE Trans Med Imag 31, 637–653 (2012).
[Crossref]

P. Mountney and G.-Z. Yang, “Dynamic view expansion for minimally invasive surgery using simultaneous localization and mapping,” Conf Proc IEEE Eng Med Biol Soc 2009, 1184–1187 (2009).
[PubMed]

Yang, J.

Yoshimura, N.

N. Yoshimura and M. B. Chancellor, “Physiology and Pharmacology of the Bladder and Urethra,” in Campbell-Walsh Urol., (Elsevier, 2009), chap. 60, pp. 1786–1833, 10 edit ed.

Zach, C.

C. Zach and M. Pollefeys, “Practical methods for convex multi-view reconstruction,” Lect Notes Comput Sc 6314, 354–367 (2010).
[Crossref]

Zeisl, B.

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

Zhang, R.

R. Zhang, P.-s. Tsai, J. E. Cryer, and M. Shah, “Shape from Shading : A Survey,” Rev. Lit. Arts Am. 21, 1–41 (1999).

Zhao, Y.

Zisserman, A.

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University Press, 2003).

Bild. Med (1)

C. Wengert, M. Reeff, P. C. Cattin, and G. Székely, “Fully Automatic Endoscope Calibration for Intraoperative Use,” Bild. Med 8, 419–423 (2006).

Biomed. Opt. Express (2)

Commun ACM (1)

M. Fischler and R. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun ACM 24, 381–395 (1981).
[Crossref]

Comput. Graph Forum (1)

R. Gal, Y. Wexler, E. Ofek, and H. Hoppe, “Seamless montage for texturing models,” Comput. Graph Forum 29, 479–486 (2010).
[Crossref]

Comput. Med. Imag. Grap. (1)

Y. Hernández-Mier, W. C. P. M. Blondel, C. Daul, D. Wolf, and F. Guillemin, “Fast construction of panoramic images for cystoscopic exploration,” Comput. Med. Imag. Grap. 34, 579–592 (2010).
[Crossref]

Comput. Vis. Image Und. (1)

A. Ben-Hamadou, C. Soussen, C. Daul, W. Blondel, and D. Wolf, “Flexible calibration of structured-light systems projecting point patterns,” Comput. Vis. Image Und. 117, 1468–1481 (2013).
[Crossref]

Conf Proc IEEE Eng Med Biol Soc (1)

P. Mountney and G.-Z. Yang, “Dynamic view expansion for minimally invasive surgery using simultaneous localization and mapping,” Conf Proc IEEE Eng Med Biol Soc 2009, 1184–1187 (2009).
[PubMed]

Eur. Urol. (1)

D. Pan and M. S. Soloway, “The importance of transurethral resection in managing patients with urothelial cancer in the bladder: Proposal for a transurethral resection of bladder tumor checklist,” Eur. Urol. 61, 1199–1203 (2012).
[Crossref] [PubMed]

IEEE Comput. Graph. Appl. Mag. (1)

M. Uyttendaele, A. Criminisi, B. Kang, S. Winder, R. Szeliski, and R. Hartley, “Image-based interactive exploration of real-world environments,” IEEE Comput. Graph. Appl. Mag. 42, 52–63 (2004).
[Crossref]

IEEE J. Biomed. Heal. informatics (1)

T. Bergen and T. M. Wittenberg, “Stitching and Surface Reconstruction from Endoscopic Image Sequences: A Review of Applications and Methods,” IEEE J. Biomed. Heal. informatics 2194, 1–20 (2014).

IEEE Robot Autom. Mag. (1)

A. Aldoma, Z. C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. Rusu, S. Gedikli, and M. Vincze, “Tutorial: Point cloud library: Three-dimensional object recognition and 6 DOF pose estimation,” IEEE Robot Autom. Mag. 19, 80–91 (2012).
[Crossref]

IEEE Trans Med Imag (1)

S. Atasoy, D. Mateus, A. Meining, G.-Z. Yang, and N. Navab, “Endoscopic video manifolds for targeted optical biopsy,” IEEE Trans Med Imag 31, 637–653 (2012).
[Crossref]

IEEE Trans. Biomed. Eng. (2)

R. Miranda-Luna, C. Daul, W. C. P. M. Blondel, Y. Hernandez-Mier, D. Wolf, and F. Guillemin, “Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm,” IEEE Trans. Biomed. Eng. 55, 541–553 (2008).
[Crossref] [PubMed]

T. D. Soper, M. P. Porter, and E. J. Seibel, “Surface mosaics of the bladder reconstructed from endoscopic video for automated surveillance,” IEEE Trans. Biomed. Eng. 59, 1670–1680 (2012).
[Crossref] [PubMed]

IEEE Trans. Med. Imaging (1)

O. G. Grasa, E. Bernal, S. Casado, I. Gil, and J. M. M. Montiel, “Visual slam for handheld monocular endoscope,” IEEE Trans. Med. Imaging 33, 135–146 (2014).
[Crossref]

IEEE Trans. Pattern Anal. Mach. Intell. (1)

Y. Boykov and V. Kolmogorov, “An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision,” IEEE Trans. Pattern Anal. Mach. Intell. 26, 1124–1137 (2004).
[Crossref]

Int. J. Comput. Vis. (2)

K. Kolev, M. Klodt, T. Brox, and D. Cremers, “Continuous global optimization in multiview 3D reconstruction,” Int. J. Comput. Vis. 84, 80–96 (2009).
[Crossref]

D. G. Lowe, “Distinctive Image Features from Scale-Invariant Keypoints,” Int. J. Comput. Vis. 60, 91–110 (2004).
[Crossref]

Int. J. Radiat. Oncol. Biol. Phys. (1)

J. C. Lindegaard, K. Tanderup, S. K. Nielsen, S. Haack, and J. Gelineck, “MRI-Guided 3D Optimization Significantly Improves DVH Parameters of Pulsed-Dose-Rate Brachytherapy in Locally Advanced Cervical Cancer,” Int. J. Radiat. Oncol. Biol. Phys. 71, 756–764 (2008).
[Crossref] [PubMed]

J. Gastrointest. Surg. (1)

Y. M. Kim, S.-E. Baek, J. S. Lim, and W. J. Hyung, “Clinical application of image-enhanced minimally invasive robotic surgery for gastric cancer: a prospective observational study,” J. Gastrointest. Surg. 17, 304–312 (2013).
[Crossref]

J. Med. Syst. (1)

I. Mehmood, M. Sajjad, and S. W. Baik, “Video summarization based tele-endoscopy: a service to efficiently manage visual data generated during wireless capsule endoscopy procedure,” J. Med. Syst. 38, 000109 (2014).
[Crossref]

Lect Notes Comput Sc (1)

C. Zach and M. Pollefeys, “Practical methods for convex multi-view reconstruction,” Lect Notes Comput Sc 6314, 354–367 (2010).
[Crossref]

Lect. Notes Comput. Sci. (1)

J. Totz, P. Mountney, D. Stoyanov, and G. Z. Yang, “Dense surface reconstruction for enhanced navigation in MIS,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics)  6891, 89–96 (2011).
[Crossref]

Med. Care (1)

G. F. Riley, A. L. Potosky, J. D. Lubitz, and L. G. Kessler, “Medicare payments from diagnosis to death for elderly cancer patients by stage at diagnosis,” Med. Care 33, 828–841 (1995).
[Crossref] [PubMed]

Med. Image Anal. (4)

L. Maier-Hein, P. Mountney, a. Bartoli, H. Elhawary, D. Elson, a. Groch, a. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, “Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery,” Med. Image Anal. 17, 974–996 (2013).
[Crossref] [PubMed]

D. Burschka, M. Li, M. Ishii, R. H. Taylor, and G. D. Hager, “Scale-invariant registration of monocular endoscopic images to CT-scans for sinus surgery,” Med. Image Anal. 9, 413–426 (2005).
[Crossref] [PubMed]

K. Mori, D. Deguchi, J. Sugiyama, Y. Suenaga, J. Toriwaki, C. R. Maurer, H. Takabatake, and H. Natori, “Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images,” Med. Image Anal. 6, 321–336 (2002).
[Crossref] [PubMed]

M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula, D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes,” Med. Image Anal. 16, 597–611 (2012).
[Crossref]

Med. Image Comput. Comput. Assist. Interv. (1)

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feussner, B. Schmauss, and J. Hornegger, “Time-of-Flight 3-D endoscopy,” Med. Image Comput. Comput. Assist. Interv. 12, 467–474 (2009).
[PubMed]

Phys. Med. Biol. (1)

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58, R37–R61 (2013).
[Crossref] [PubMed]

PLOS ONE (1)

M. Agenant, H.-J. Noordmans, W. Koomen, and J. L. H. R. Bosch, “Real-time bladder lesion registration and navigation: a phantom study,” PLOS ONE 8, e54348 (2013).
[Crossref] [PubMed]

Proc IEEE Comput. Vis. Pattern Recognit. (1)

D. Nistér and H. Stewénius, “Scalable Recognition with a Vocabulary Tree,” Proc IEEE Comput. Vis. Pattern Recognit. 2, 2161–2168 (2006).

Rev. Lit. Arts Am. (1)

R. Zhang, P.-s. Tsai, J. E. Cryer, and M. Shah, “Shape from Shading : A Survey,” Rev. Lit. Arts Am. 21, 1–41 (1999).

SIBGRAPI (1)

C. Q. Forster and C. Tozzi, “Towards 3D reconstruction of endoscope images using shape from shading,” SIBGRAPI 200090–96 (2000).

Symp Geom Process (1)

M. Kazhdan, M. Bolitho, and H. Hoppe, “Poisson surface reconstruction,” Symp Geom Process 7, 61–70 (2006).

Vis. Algorithms (1)

B. Triggs and P. McLauchlan, “Bundle adjustment: a modern synthesis,” Vis. Algorithms 1883, 298–372 (2000).

Other (7)

H. Strasdat, J. M. M. Montiel, and A. J. Davison, “Real-time monocular SLAM: Why filter?” IEEE Int Conf Robot Autom pp. 2657–2664 (2010).

M. Waechter, N. Moehrle, and M. Goesele, “Let There Be Color! Large-Scale Texturing of 3D Reconstructions,” Proc ECCV pp. 836–850 (2014).

J.-Y. Bouguet, “Camera calibration toolbox for matlab,” ( http://www.vision.caltech.edu/bouguetj/calib_doc/ ) (2004).

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University Press, 2003).

N. Yoshimura and M. B. Chancellor, “Physiology and Pharmacology of the Bladder and Urethra,” in Campbell-Walsh Urol., (Elsevier, 2009), chap. 60, pp. 1786–1833, 10 edit ed.

A. Ben-Hamadou, C. Daul, C. Soussen, A. Rekik, and W. Blondel, “A novel 3D surface construction approach: Appliciation to 3D endoscopic data,” Conf Proc IEEE Image Proc pp. 4425–4428 (2010).

A. Behrens, T. Stehle, S. Gross, and T. Aach, “Local and global panoramic imaging for fluorescence bladder endoscopy,” Conf Proc IEEE Eng Med Biol Soc pp. 6990–6993 (2009).

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Figures (4)

Fig. 1
Fig. 1

Overview of the four-step 3D reconstruction algorithm. The gray inset highlights the sub-steps of the image preprocessing step. Black boxes indicate major steps and white boxes indicate the inputs and outputs for each step. SfM: Structure from motion TEX: texture reconstruction.

Fig. 2
Fig. 2

Phantom reconstruction results. Top row (blue background): original semi-cylinder phantom; bottom row (orange background): modified semi-cylinder phantom. (a) Standard digital camera images of the phantoms highlighting their shaped are compared with the (b) untextured reconstructed mesh. (c) Cross-sections of the expected mesh (dotted black line) and average reconstructed cross section (red) are compared. The pink region represents ±1 standard deviation of error about the average cross section. Each box of the grid represents 1 cm2. (d) Standard digital camera images of the phantoms highlighting their surface appearance compared with (e) the reconstructed textured phantoms viewed from approximately the same camera angles. Black arrows are added to highlight similar features between the original and reconstructed images. Side walls of the phantom removed in (b) and (e) to accentuate the cylindrical portion. Green boxes indicate regions of texture shown in greater detail in (f), and emphasize the seamlessness between regions composed of different images. The dotted white lines in (f) indicate boundaries between mesh faces that are composed of different original images.

Fig. 3
Fig. 3

Output from individual steps of the reconstruction pipeline from a clinical dataset of human bladder: (a) a representative, original WLC image, (b) point cloud from the structure-from-motion step before outlier removal, (c) mesh from the mesh-generation step, and (d) labeled texture (faces with the same color are labeled with the same input image) and (e–f) textured mesh from texture-generation steps. The green box shows a similar region between subfigures (d–f) indicating clear continuity of vessels despite the use of multiple input images to construct this region. The green box is approximately the size of a single WLC image. Black arrows in (a) and (f) indicate similar regions of the bladder.

Fig. 4
Fig. 4

Reconstruction from a clinical dataset of human bladder. Sub-figures show views from the (a) anterior, (b) posterior, (c) left lateral, and (d) right lateral walls. Black circle and arrow in (c) show regions of a papillary tumor and scarring, respectively. Regions that appear dark represent the interior of the bladder. Video 1 shows a fly-through of the full reconstruction.

Tables (1)

Tables Icon

Table 1 Algorithm run-time of reconstruction pipeline for all successfully reconstructed datasets and example dataset from Fig. 4. Times given in MM:SS format

Equations (2)

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

min R , t , X ( i , j ) Ω x j i Π ( K ( R i X j + t i ) ) 2 2 ,
E ( l ) = Σ f i faces E d ( f i , l i ) + Σ ( f i , f j ) Edges E s ( f i , f j , l i , l j ) .