Abstract

New advances in wide-angle cytometry have allowed researchers to obtain micro- and nano-structural information from biological cells. While the complex two-dimensional scattering patterns generated by these devices contain vital information about the structure of a cell, no computational analysis methods have been developed to rapidly extract this information. In this work we demonstrate a multi-agent computational pipeline that is able to extract features from a two-dimensional laser scattering image, cluster these features into spatially distinct regions, and extract a set of parameters relating to the structure of intensity regions within the image. This parameterization can then be used to infer medically relevant properties of the scattering object.

© 2006 Optical Society of America

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2006 (3)

K. Singh, X. Su, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "A Miniaturized Wide-Angle 2D Cytometer," Cytometry A 69A, 307-315 (2006).

M. G. H. Omran, A. Salman, and A. P. Engelbrecht, "Dynamic clustering using particle swarm optimization with application in image segmentation," Pattern Anal. Appl. 8, 332-344 (2006).
[CrossRef]

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

2005 (5)

L. Bergman, A. Verikas, and M. Bacauskiene, "Unsupervised colour image segmentation applied to printing quality assessment," Image Vision Comput. 23, 417-425 (2005).
[CrossRef]

V. Navalpakkam and L. Itti, "Modeling the influence of task on attention," Vision Res. 45, 205-231 (2005).
[CrossRef]

B. Prasad, S. Du, W. Badawy, and K. Kaler, "A real-time multiple-cell tracking platform for dielectrophoresis (DEP)-based cellular analysis," Meas. Sci. Technol. 16, 909-924 (2005).
[CrossRef]

T. Mirzayans, N. Parimi, P. Pilarski, C. Backhouse, L. Wyard-Scott, and P. Musilek, "A swarm-based system for object recognition," Neural Netw. World 15, 243-255 (2005).

P. L. Gourley and R. K. Naviaux, "Optical Phenotyping of Human Mitochondria in a Biocavity Laser," IEEE J. Quantum Electron. 11, 818-826 (2005).
[CrossRef]

2004 (4)

K. Singh, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "Analysis of Cellular Structure by Light Scattering Measurements in a New Cytometer Design Based on a Liquid-CoreWaveguide," IEE Proc.-Nanobiotechnol. 151, 10-16 (2004).
[CrossRef]

N. Richard, M. Dojat, and C. Garbay, "Automated segmentation of human brain MR images using a multi-agent approach," Artif. Intell. Med. 30, 153-175 (2004).
[CrossRef] [PubMed]

E. G. P. Bovenkamp, J. Dijkstra, J. G. Bosch, and J. H. C. Reiber, "Multi-agent segmentation of IVUS images," Pattern Recogn. 37, 647-663 (2004).
[CrossRef]

M. P. Wachowiak, R. Smolikova, Y. F. Zheng, J. M. Zurada, and A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization," IEEE Trans. Evol. Comput. 8, 289-301 (2004).
[CrossRef]

2003 (2)

P. L. Gourley, "Biocavity laser for high-speed cell and tumour biology," J. Phys. D-Appl. Phys. 36, R228-R239 (2003).
[CrossRef]

A. Broggi, M. Cellario, P. Lombardi, and M. Porta, "An evolutionary approach to visual sensing for vehicle navigation," IEEE Trans. Ind. Electron. 50, 18-29 (2003).
[CrossRef]

2002 (2)

Y. Wang and B. Yuan, "Fast method for face location and tracking by distributed behaviour-based agents," IEE Proc.-Vis. Image Signal Process. 149, 173-178 (2002).
[CrossRef]

J. M. Liu, H. Jing, and Y. Y. Tang, "Multi-agent oriented constraint satisfaction," Artif. Intell. 136, 101-144 (2002).
[CrossRef]

2000 (5)

V. P. Maltsev, "Scanning flow cytometry for individual particle analysis," Rev. Sci. Instrum. 71, 243-255 (2000).
[CrossRef]

P. Chacon, J. F. Diaz, F. Moran, and J. M. Andreu, "Reconstruction of protein form with X-ray solution scattering and a genetic algorithm," J. Mol. Biol. 299, 1289-1302 (2000).
[CrossRef] [PubMed]

K. A. Sem’yanov, P. A. Tarasov, J. T. Soini, A. K. Petrov, and V. P. Maltsev, "Calibration-free method to determine the size and hemoglobin concentration of individual red blood cells from light scattering," Appl. Opt. 39, 5884- 5889 (2000).
[CrossRef]

R. Drezek, A. Dunn, and R. Richards-Kortum, "A pulsed finite-difference time-domain (FDTD) method for calculating light scattering from biological cells over broad wavelength ranges," Opt. Express 6, 147-157 (2000), http://www.opticsinfobase.org/abstract.cfm?URI=oe-6-7-147.
[CrossRef] [PubMed]

K. Sem’yanov and V. P. Maltsev, "Analysis of sub-micron spherical particles using scanning flow cytometry," Part. Part. Syst. Charact. 17, 225-229 (2000).
[CrossRef]

1999 (4)

R. Drezek, A. Dunn, and R. Richards-Kortum, "Light scattering from cells: finite-difference time-domain simulations and goniometric measurements," Appl. Opt. 38, 3651-3661 (1999).
[CrossRef]

T. Ojala and M. Pietikainen, "Unsupervised texture segmentation using feature distributions," Pattern Recogn. 32, 477-486 (1999).
[CrossRef]

J. M. Liu and Y. Y. Tang, "Adaptive image segmentation with distributed behavior-based agents," IEEE Trans. Pattern Anal. Mach. Intell. 21, 544-551 (1999).
[CrossRef]

M. Meister and M. Berry, "The Neural Code of the Retina," Neuron 22, 435-450 (1999).
[CrossRef] [PubMed]

1998 (3)

L. Itti, C. Koch, and E. Niebur, "A model of saliency-based visual attention for rapid scene analysis," IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254-1259 (1998).
[CrossRef]

Z. Ulanowski, Z. Wang, P. H. Kaye, and I. K. Ludlow, "Application of neural networks to the inverse scattering problem for spheres," Appl. Opt. 37, 4027-4033 (1998).
[CrossRef]

P. Chacon, F. Moran, J. F. Diaz, E. Pantos, and J. M. Andreu, "Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm," Biophys. J. 74, 2760-2775 (1998).
[CrossRef] [PubMed]

1997 (2)

J. Liu, Y. Y. Tang, and Y. C. Cao, "An evolutionary autonomous agents approach to image feature extraction," IEEE Trans. Evol. Comput. 1, 141-158 (1997).
[CrossRef]

C. E. Priebe, D. J. Marchette, and G. W. Rogers, "Segmentation of random fields via borrowed strength density estimation," IEEE Trans. Pattern Anal. Mach. Intell. 19, 494-499 (1997).
[CrossRef]

1996 (1)

A. K. Jain and K. Karu, "Learning texture discrimination masks," IEEE Trans. Pattern Anal. Mach. Intell. 18, 195-205 (1996).
[CrossRef]

1995 (1)

D. K. Panjwani and G. Healey, "Markov Random-Field Models For Unsupervised Segmentation Of Textured Color Images," IEEE Trans. Pattern Anal. Mach. Intell. 17, 939-954 (1995).
[CrossRef]

1993 (1)

N. Pal and S. Pal, "A review on image segmentation techniques," Pattern Recognit. 26, 1277-1294 (1993).
[CrossRef]

1992 (1)

X. L. Wu, "Image-Coding By Adaptive Tree-Structured Segmentation," IEEE Trans. Inf. Theory 38, 1755-1767 (1992).
[CrossRef]

1953 (1)

J. D. Watson and F. H. C. Crick, "Molecular Structure Of Nucleic Acids - A Structure For Deoxyribose Nucleic Acid," Nature 171, 737-738 (1953).
[CrossRef] [PubMed]

Andreu, J. M.

P. Chacon, J. F. Diaz, F. Moran, and J. M. Andreu, "Reconstruction of protein form with X-ray solution scattering and a genetic algorithm," J. Mol. Biol. 299, 1289-1302 (2000).
[CrossRef] [PubMed]

P. Chacon, F. Moran, J. F. Diaz, E. Pantos, and J. M. Andreu, "Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm," Biophys. J. 74, 2760-2775 (1998).
[CrossRef] [PubMed]

Bacauskiene, M.

L. Bergman, A. Verikas, and M. Bacauskiene, "Unsupervised colour image segmentation applied to printing quality assessment," Image Vision Comput. 23, 417-425 (2005).
[CrossRef]

Backhouse, C.

T. Mirzayans, N. Parimi, P. Pilarski, C. Backhouse, L. Wyard-Scott, and P. Musilek, "A swarm-based system for object recognition," Neural Netw. World 15, 243-255 (2005).

Backhouse, C. J.

K. Singh, X. Su, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "A Miniaturized Wide-Angle 2D Cytometer," Cytometry A 69A, 307-315 (2006).

K. Singh, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "Analysis of Cellular Structure by Light Scattering Measurements in a New Cytometer Design Based on a Liquid-CoreWaveguide," IEE Proc.-Nanobiotechnol. 151, 10-16 (2004).
[CrossRef]

Badawy, W.

B. Prasad, S. Du, W. Badawy, and K. Kaler, "A real-time multiple-cell tracking platform for dielectrophoresis (DEP)-based cellular analysis," Meas. Sci. Technol. 16, 909-924 (2005).
[CrossRef]

Bergman, L.

L. Bergman, A. Verikas, and M. Bacauskiene, "Unsupervised colour image segmentation applied to printing quality assessment," Image Vision Comput. 23, 417-425 (2005).
[CrossRef]

Berry, M.

M. Meister and M. Berry, "The Neural Code of the Retina," Neuron 22, 435-450 (1999).
[CrossRef] [PubMed]

Bosch, J. G.

E. G. P. Bovenkamp, J. Dijkstra, J. G. Bosch, and J. H. C. Reiber, "Multi-agent segmentation of IVUS images," Pattern Recogn. 37, 647-663 (2004).
[CrossRef]

Bovenkamp, E. G. P.

E. G. P. Bovenkamp, J. Dijkstra, J. G. Bosch, and J. H. C. Reiber, "Multi-agent segmentation of IVUS images," Pattern Recogn. 37, 647-663 (2004).
[CrossRef]

Broggi, A.

A. Broggi, M. Cellario, P. Lombardi, and M. Porta, "An evolutionary approach to visual sensing for vehicle navigation," IEEE Trans. Ind. Electron. 50, 18-29 (2003).
[CrossRef]

Cao, Y. C.

J. Liu, Y. Y. Tang, and Y. C. Cao, "An evolutionary autonomous agents approach to image feature extraction," IEEE Trans. Evol. Comput. 1, 141-158 (1997).
[CrossRef]

Capjack, C.

K. Singh, X. Su, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "A Miniaturized Wide-Angle 2D Cytometer," Cytometry A 69A, 307-315 (2006).

K. Singh, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "Analysis of Cellular Structure by Light Scattering Measurements in a New Cytometer Design Based on a Liquid-CoreWaveguide," IEE Proc.-Nanobiotechnol. 151, 10-16 (2004).
[CrossRef]

Cellario, M.

A. Broggi, M. Cellario, P. Lombardi, and M. Porta, "An evolutionary approach to visual sensing for vehicle navigation," IEEE Trans. Ind. Electron. 50, 18-29 (2003).
[CrossRef]

Chacon, P.

P. Chacon, J. F. Diaz, F. Moran, and J. M. Andreu, "Reconstruction of protein form with X-ray solution scattering and a genetic algorithm," J. Mol. Biol. 299, 1289-1302 (2000).
[CrossRef] [PubMed]

P. Chacon, F. Moran, J. F. Diaz, E. Pantos, and J. M. Andreu, "Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm," Biophys. J. 74, 2760-2775 (1998).
[CrossRef] [PubMed]

Crick, F. H. C.

J. D. Watson and F. H. C. Crick, "Molecular Structure Of Nucleic Acids - A Structure For Deoxyribose Nucleic Acid," Nature 171, 737-738 (1953).
[CrossRef] [PubMed]

Currie, L. M.

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Diaz, J. F.

P. Chacon, J. F. Diaz, F. Moran, and J. M. Andreu, "Reconstruction of protein form with X-ray solution scattering and a genetic algorithm," J. Mol. Biol. 299, 1289-1302 (2000).
[CrossRef] [PubMed]

P. Chacon, F. Moran, J. F. Diaz, E. Pantos, and J. M. Andreu, "Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm," Biophys. J. 74, 2760-2775 (1998).
[CrossRef] [PubMed]

Dijkstra, J.

E. G. P. Bovenkamp, J. Dijkstra, J. G. Bosch, and J. H. C. Reiber, "Multi-agent segmentation of IVUS images," Pattern Recogn. 37, 647-663 (2004).
[CrossRef]

Dojat, M.

N. Richard, M. Dojat, and C. Garbay, "Automated segmentation of human brain MR images using a multi-agent approach," Artif. Intell. Med. 30, 153-175 (2004).
[CrossRef] [PubMed]

Drezek, R.

Du, S.

B. Prasad, S. Du, W. Badawy, and K. Kaler, "A real-time multiple-cell tracking platform for dielectrophoresis (DEP)-based cellular analysis," Meas. Sci. Technol. 16, 909-924 (2005).
[CrossRef]

Dunn, A.

Elmaghraby, A. S.

M. P. Wachowiak, R. Smolikova, Y. F. Zheng, J. M. Zurada, and A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization," IEEE Trans. Evol. Comput. 8, 289-301 (2004).
[CrossRef]

Engelbrecht, A. P.

M. G. H. Omran, A. Salman, and A. P. Engelbrecht, "Dynamic clustering using particle swarm optimization with application in image segmentation," Pattern Anal. Appl. 8, 332-344 (2006).
[CrossRef]

Garbay, C.

N. Richard, M. Dojat, and C. Garbay, "Automated segmentation of human brain MR images using a multi-agent approach," Artif. Intell. Med. 30, 153-175 (2004).
[CrossRef] [PubMed]

Gourley, P. L.

P. L. Gourley and R. K. Naviaux, "Optical Phenotyping of Human Mitochondria in a Biocavity Laser," IEEE J. Quantum Electron. 11, 818-826 (2005).
[CrossRef]

P. L. Gourley, "Biocavity laser for high-speed cell and tumour biology," J. Phys. D-Appl. Phys. 36, R228-R239 (2003).
[CrossRef]

Healey, G.

D. K. Panjwani and G. Healey, "Markov Random-Field Models For Unsupervised Segmentation Of Textured Color Images," IEEE Trans. Pattern Anal. Mach. Intell. 17, 939-954 (1995).
[CrossRef]

Hirsch, B. E.

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Imielinska, C.

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Itti, L.

V. Navalpakkam and L. Itti, "Modeling the influence of task on attention," Vision Res. 45, 205-231 (2005).
[CrossRef]

L. Itti, C. Koch, and E. Niebur, "A model of saliency-based visual attention for rapid scene analysis," IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254-1259 (1998).
[CrossRef]

Jain, A. K.

A. K. Jain and K. Karu, "Learning texture discrimination masks," IEEE Trans. Pattern Anal. Mach. Intell. 18, 195-205 (1996).
[CrossRef]

Jing, H.

J. M. Liu, H. Jing, and Y. Y. Tang, "Multi-agent oriented constraint satisfaction," Artif. Intell. 136, 101-144 (2002).
[CrossRef]

Kaler, K.

B. Prasad, S. Du, W. Badawy, and K. Kaler, "A real-time multiple-cell tracking platform for dielectrophoresis (DEP)-based cellular analysis," Meas. Sci. Technol. 16, 909-924 (2005).
[CrossRef]

Karu, K.

A. K. Jain and K. Karu, "Learning texture discrimination masks," IEEE Trans. Pattern Anal. Mach. Intell. 18, 195-205 (1996).
[CrossRef]

Kaye, P. H.

Koch, C.

L. Itti, C. Koch, and E. Niebur, "A model of saliency-based visual attention for rapid scene analysis," IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254-1259 (1998).
[CrossRef]

LeBlanc, V. R.

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Liu, C.

K. Singh, X. Su, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "A Miniaturized Wide-Angle 2D Cytometer," Cytometry A 69A, 307-315 (2006).

K. Singh, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "Analysis of Cellular Structure by Light Scattering Measurements in a New Cytometer Design Based on a Liquid-CoreWaveguide," IEE Proc.-Nanobiotechnol. 151, 10-16 (2004).
[CrossRef]

Liu, J.

J. Liu, Y. Y. Tang, and Y. C. Cao, "An evolutionary autonomous agents approach to image feature extraction," IEEE Trans. Evol. Comput. 1, 141-158 (1997).
[CrossRef]

Liu, J. M.

J. M. Liu, H. Jing, and Y. Y. Tang, "Multi-agent oriented constraint satisfaction," Artif. Intell. 136, 101-144 (2002).
[CrossRef]

J. M. Liu and Y. Y. Tang, "Adaptive image segmentation with distributed behavior-based agents," IEEE Trans. Pattern Anal. Mach. Intell. 21, 544-551 (1999).
[CrossRef]

Lombardi, P.

A. Broggi, M. Cellario, P. Lombardi, and M. Porta, "An evolutionary approach to visual sensing for vehicle navigation," IEEE Trans. Ind. Electron. 50, 18-29 (2003).
[CrossRef]

Ludlow, I. K.

Maltsev, V. P.

K. A. Sem’yanov, P. A. Tarasov, J. T. Soini, A. K. Petrov, and V. P. Maltsev, "Calibration-free method to determine the size and hemoglobin concentration of individual red blood cells from light scattering," Appl. Opt. 39, 5884- 5889 (2000).
[CrossRef]

V. P. Maltsev, "Scanning flow cytometry for individual particle analysis," Rev. Sci. Instrum. 71, 243-255 (2000).
[CrossRef]

K. Sem’yanov and V. P. Maltsev, "Analysis of sub-micron spherical particles using scanning flow cytometry," Part. Part. Syst. Charact. 17, 225-229 (2000).
[CrossRef]

Marchette, D. J.

C. E. Priebe, D. J. Marchette, and G. W. Rogers, "Segmentation of random fields via borrowed strength density estimation," IEEE Trans. Pattern Anal. Mach. Intell. 19, 494-499 (1997).
[CrossRef]

Meister, M.

M. Meister and M. Berry, "The Neural Code of the Retina," Neuron 22, 435-450 (1999).
[CrossRef] [PubMed]

Mirzayans, T.

T. Mirzayans, N. Parimi, P. Pilarski, C. Backhouse, L. Wyard-Scott, and P. Musilek, "A swarm-based system for object recognition," Neural Netw. World 15, 243-255 (2005).

Moran, F.

P. Chacon, J. F. Diaz, F. Moran, and J. M. Andreu, "Reconstruction of protein form with X-ray solution scattering and a genetic algorithm," J. Mol. Biol. 299, 1289-1302 (2000).
[CrossRef] [PubMed]

P. Chacon, F. Moran, J. F. Diaz, E. Pantos, and J. M. Andreu, "Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm," Biophys. J. 74, 2760-2775 (1998).
[CrossRef] [PubMed]

Musilek, P.

T. Mirzayans, N. Parimi, P. Pilarski, C. Backhouse, L. Wyard-Scott, and P. Musilek, "A swarm-based system for object recognition," Neural Netw. World 15, 243-255 (2005).

Navalpakkam, V.

V. Navalpakkam and L. Itti, "Modeling the influence of task on attention," Vision Res. 45, 205-231 (2005).
[CrossRef]

Naviaux, R. K.

P. L. Gourley and R. K. Naviaux, "Optical Phenotyping of Human Mitochondria in a Biocavity Laser," IEEE J. Quantum Electron. 11, 818-826 (2005).
[CrossRef]

Niebur, E.

L. Itti, C. Koch, and E. Niebur, "A model of saliency-based visual attention for rapid scene analysis," IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254-1259 (1998).
[CrossRef]

Ojala, T.

T. Ojala and M. Pietikainen, "Unsupervised texture segmentation using feature distributions," Pattern Recogn. 32, 477-486 (1999).
[CrossRef]

Omran, M. G. H.

M. G. H. Omran, A. Salman, and A. P. Engelbrecht, "Dynamic clustering using particle swarm optimization with application in image segmentation," Pattern Anal. Appl. 8, 332-344 (2006).
[CrossRef]

Pal, N.

N. Pal and S. Pal, "A review on image segmentation techniques," Pattern Recognit. 26, 1277-1294 (1993).
[CrossRef]

Pal, S.

N. Pal and S. Pal, "A review on image segmentation techniques," Pattern Recognit. 26, 1277-1294 (1993).
[CrossRef]

Panjwani, D. K.

D. K. Panjwani and G. Healey, "Markov Random-Field Models For Unsupervised Segmentation Of Textured Color Images," IEEE Trans. Pattern Anal. Mach. Intell. 17, 939-954 (1995).
[CrossRef]

Pantos, E.

P. Chacon, F. Moran, J. F. Diaz, E. Pantos, and J. M. Andreu, "Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm," Biophys. J. 74, 2760-2775 (1998).
[CrossRef] [PubMed]

Parimi, N.

T. Mirzayans, N. Parimi, P. Pilarski, C. Backhouse, L. Wyard-Scott, and P. Musilek, "A swarm-based system for object recognition," Neural Netw. World 15, 243-255 (2005).

Petrov, A. K.

Pietikainen, M.

T. Ojala and M. Pietikainen, "Unsupervised texture segmentation using feature distributions," Pattern Recogn. 32, 477-486 (1999).
[CrossRef]

Pilarski, P.

T. Mirzayans, N. Parimi, P. Pilarski, C. Backhouse, L. Wyard-Scott, and P. Musilek, "A swarm-based system for object recognition," Neural Netw. World 15, 243-255 (2005).

Porta, M.

A. Broggi, M. Cellario, P. Lombardi, and M. Porta, "An evolutionary approach to visual sensing for vehicle navigation," IEEE Trans. Ind. Electron. 50, 18-29 (2003).
[CrossRef]

Prasad, B.

B. Prasad, S. Du, W. Badawy, and K. Kaler, "A real-time multiple-cell tracking platform for dielectrophoresis (DEP)-based cellular analysis," Meas. Sci. Technol. 16, 909-924 (2005).
[CrossRef]

Priebe, C. E.

C. E. Priebe, D. J. Marchette, and G. W. Rogers, "Segmentation of random fields via borrowed strength density estimation," IEEE Trans. Pattern Anal. Mach. Intell. 19, 494-499 (1997).
[CrossRef]

Reiber, J. H. C.

E. G. P. Bovenkamp, J. Dijkstra, J. G. Bosch, and J. H. C. Reiber, "Multi-agent segmentation of IVUS images," Pattern Recogn. 37, 647-663 (2004).
[CrossRef]

Richard, N.

N. Richard, M. Dojat, and C. Garbay, "Automated segmentation of human brain MR images using a multi-agent approach," Artif. Intell. Med. 30, 153-175 (2004).
[CrossRef] [PubMed]

Richards-Kortum, R.

Rogers, G. W.

C. E. Priebe, D. J. Marchette, and G. W. Rogers, "Segmentation of random fields via borrowed strength density estimation," IEEE Trans. Pattern Anal. Mach. Intell. 19, 494-499 (1997).
[CrossRef]

Rozmus, W.

K. Singh, X. Su, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "A Miniaturized Wide-Angle 2D Cytometer," Cytometry A 69A, 307-315 (2006).

K. Singh, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "Analysis of Cellular Structure by Light Scattering Measurements in a New Cytometer Design Based on a Liquid-CoreWaveguide," IEE Proc.-Nanobiotechnol. 151, 10-16 (2004).
[CrossRef]

Salman, A.

M. G. H. Omran, A. Salman, and A. P. Engelbrecht, "Dynamic clustering using particle swarm optimization with application in image segmentation," Pattern Anal. Appl. 8, 332-344 (2006).
[CrossRef]

Schmidt, H.

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Sem’yanov, K.

K. Sem’yanov and V. P. Maltsev, "Analysis of sub-micron spherical particles using scanning flow cytometry," Part. Part. Syst. Charact. 17, 225-229 (2000).
[CrossRef]

Sem’yanov, K. A.

Singh, K.

K. Singh, X. Su, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "A Miniaturized Wide-Angle 2D Cytometer," Cytometry A 69A, 307-315 (2006).

K. Singh, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "Analysis of Cellular Structure by Light Scattering Measurements in a New Cytometer Design Based on a Liquid-CoreWaveguide," IEE Proc.-Nanobiotechnol. 151, 10-16 (2004).
[CrossRef]

Smolikova, R.

M. P. Wachowiak, R. Smolikova, Y. F. Zheng, J. M. Zurada, and A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization," IEEE Trans. Evol. Comput. 8, 289-301 (2004).
[CrossRef]

Soini, J. T.

Su, X.

K. Singh, X. Su, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "A Miniaturized Wide-Angle 2D Cytometer," Cytometry A 69A, 307-315 (2006).

Tang, Y. Y.

J. M. Liu, H. Jing, and Y. Y. Tang, "Multi-agent oriented constraint satisfaction," Artif. Intell. 136, 101-144 (2002).
[CrossRef]

J. M. Liu and Y. Y. Tang, "Adaptive image segmentation with distributed behavior-based agents," IEEE Trans. Pattern Anal. Mach. Intell. 21, 544-551 (1999).
[CrossRef]

J. Liu, Y. Y. Tang, and Y. C. Cao, "An evolutionary autonomous agents approach to image feature extraction," IEEE Trans. Evol. Comput. 1, 141-158 (1997).
[CrossRef]

Tarasov, P. A.

Udupa, J. K.

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Ulanowski, Z.

Verikas, A.

L. Bergman, A. Verikas, and M. Bacauskiene, "Unsupervised colour image segmentation applied to printing quality assessment," Image Vision Comput. 23, 417-425 (2005).
[CrossRef]

Wachowiak, M. P.

M. P. Wachowiak, R. Smolikova, Y. F. Zheng, J. M. Zurada, and A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization," IEEE Trans. Evol. Comput. 8, 289-301 (2004).
[CrossRef]

Wang, Y.

Y. Wang and B. Yuan, "Fast method for face location and tracking by distributed behaviour-based agents," IEE Proc.-Vis. Image Signal Process. 149, 173-178 (2002).
[CrossRef]

Wang, Z.

Watson, J. D.

J. D. Watson and F. H. C. Crick, "Molecular Structure Of Nucleic Acids - A Structure For Deoxyribose Nucleic Acid," Nature 171, 737-738 (1953).
[CrossRef] [PubMed]

Woodburn, J.

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Wu, X. L.

X. L. Wu, "Image-Coding By Adaptive Tree-Structured Segmentation," IEEE Trans. Inf. Theory 38, 1755-1767 (1992).
[CrossRef]

Wyard-Scott, L.

T. Mirzayans, N. Parimi, P. Pilarski, C. Backhouse, L. Wyard-Scott, and P. Musilek, "A swarm-based system for object recognition," Neural Netw. World 15, 243-255 (2005).

Ying, Z. G.

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Yuan, B.

Y. Wang and B. Yuan, "Fast method for face location and tracking by distributed behaviour-based agents," IEE Proc.-Vis. Image Signal Process. 149, 173-178 (2002).
[CrossRef]

Zheng, Y. F.

M. P. Wachowiak, R. Smolikova, Y. F. Zheng, J. M. Zurada, and A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization," IEEE Trans. Evol. Comput. 8, 289-301 (2004).
[CrossRef]

Zurada, J. M.

M. P. Wachowiak, R. Smolikova, Y. F. Zheng, J. M. Zurada, and A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization," IEEE Trans. Evol. Comput. 8, 289-301 (2004).
[CrossRef]

Appl. Opt. (3)

Artif. Intell. (1)

J. M. Liu, H. Jing, and Y. Y. Tang, "Multi-agent oriented constraint satisfaction," Artif. Intell. 136, 101-144 (2002).
[CrossRef]

Artif. Intell. Med. (1)

N. Richard, M. Dojat, and C. Garbay, "Automated segmentation of human brain MR images using a multi-agent approach," Artif. Intell. Med. 30, 153-175 (2004).
[CrossRef] [PubMed]

Biophys. J. (1)

P. Chacon, F. Moran, J. F. Diaz, E. Pantos, and J. M. Andreu, "Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm," Biophys. J. 74, 2760-2775 (1998).
[CrossRef] [PubMed]

Comput. Med. Imaging Graph. (1)

J. K. Udupa, V. R. LeBlanc, Z. G. Ying, C. Imielinska, H. Schmidt, L. M. Currie, B. E. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comput. Med. Imaging Graph. 30(2), 75-87 (2006).
[CrossRef] [PubMed]

Cytometry A (1)

K. Singh, X. Su, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "A Miniaturized Wide-Angle 2D Cytometer," Cytometry A 69A, 307-315 (2006).

IEE Proc.-Vis. Image Signal Process. (1)

Y. Wang and B. Yuan, "Fast method for face location and tracking by distributed behaviour-based agents," IEE Proc.-Vis. Image Signal Process. 149, 173-178 (2002).
[CrossRef]

IEEE J. Quantum Electron. (1)

P. L. Gourley and R. K. Naviaux, "Optical Phenotyping of Human Mitochondria in a Biocavity Laser," IEEE J. Quantum Electron. 11, 818-826 (2005).
[CrossRef]

IEEE Trans. Evol. Comput. (2)

J. Liu, Y. Y. Tang, and Y. C. Cao, "An evolutionary autonomous agents approach to image feature extraction," IEEE Trans. Evol. Comput. 1, 141-158 (1997).
[CrossRef]

M. P. Wachowiak, R. Smolikova, Y. F. Zheng, J. M. Zurada, and A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization," IEEE Trans. Evol. Comput. 8, 289-301 (2004).
[CrossRef]

IEEE Trans. Ind. Electron. (1)

A. Broggi, M. Cellario, P. Lombardi, and M. Porta, "An evolutionary approach to visual sensing for vehicle navigation," IEEE Trans. Ind. Electron. 50, 18-29 (2003).
[CrossRef]

IEEE Trans. Inf. Theory (1)

X. L. Wu, "Image-Coding By Adaptive Tree-Structured Segmentation," IEEE Trans. Inf. Theory 38, 1755-1767 (1992).
[CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell. (5)

L. Itti, C. Koch, and E. Niebur, "A model of saliency-based visual attention for rapid scene analysis," IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254-1259 (1998).
[CrossRef]

J. M. Liu and Y. Y. Tang, "Adaptive image segmentation with distributed behavior-based agents," IEEE Trans. Pattern Anal. Mach. Intell. 21, 544-551 (1999).
[CrossRef]

D. K. Panjwani and G. Healey, "Markov Random-Field Models For Unsupervised Segmentation Of Textured Color Images," IEEE Trans. Pattern Anal. Mach. Intell. 17, 939-954 (1995).
[CrossRef]

A. K. Jain and K. Karu, "Learning texture discrimination masks," IEEE Trans. Pattern Anal. Mach. Intell. 18, 195-205 (1996).
[CrossRef]

C. E. Priebe, D. J. Marchette, and G. W. Rogers, "Segmentation of random fields via borrowed strength density estimation," IEEE Trans. Pattern Anal. Mach. Intell. 19, 494-499 (1997).
[CrossRef]

Image Vision Comput. (1)

L. Bergman, A. Verikas, and M. Bacauskiene, "Unsupervised colour image segmentation applied to printing quality assessment," Image Vision Comput. 23, 417-425 (2005).
[CrossRef]

J. Mol. Biol. (1)

P. Chacon, J. F. Diaz, F. Moran, and J. M. Andreu, "Reconstruction of protein form with X-ray solution scattering and a genetic algorithm," J. Mol. Biol. 299, 1289-1302 (2000).
[CrossRef] [PubMed]

J. Phys. D-Appl. Phys. (1)

P. L. Gourley, "Biocavity laser for high-speed cell and tumour biology," J. Phys. D-Appl. Phys. 36, R228-R239 (2003).
[CrossRef]

Meas. Sci. Technol. (1)

B. Prasad, S. Du, W. Badawy, and K. Kaler, "A real-time multiple-cell tracking platform for dielectrophoresis (DEP)-based cellular analysis," Meas. Sci. Technol. 16, 909-924 (2005).
[CrossRef]

Nanobiotechnol. (1)

K. Singh, C. Liu, C. Capjack, W. Rozmus, and C. J. Backhouse, "Analysis of Cellular Structure by Light Scattering Measurements in a New Cytometer Design Based on a Liquid-CoreWaveguide," IEE Proc.-Nanobiotechnol. 151, 10-16 (2004).
[CrossRef]

Nature (1)

J. D. Watson and F. H. C. Crick, "Molecular Structure Of Nucleic Acids - A Structure For Deoxyribose Nucleic Acid," Nature 171, 737-738 (1953).
[CrossRef] [PubMed]

Neural Netw. World (1)

T. Mirzayans, N. Parimi, P. Pilarski, C. Backhouse, L. Wyard-Scott, and P. Musilek, "A swarm-based system for object recognition," Neural Netw. World 15, 243-255 (2005).

Neuron (1)

M. Meister and M. Berry, "The Neural Code of the Retina," Neuron 22, 435-450 (1999).
[CrossRef] [PubMed]

Opt. Express (1)

Part. Part. Syst. Charact. (1)

K. Sem’yanov and V. P. Maltsev, "Analysis of sub-micron spherical particles using scanning flow cytometry," Part. Part. Syst. Charact. 17, 225-229 (2000).
[CrossRef]

Pattern Anal. Appl. (1)

M. G. H. Omran, A. Salman, and A. P. Engelbrecht, "Dynamic clustering using particle swarm optimization with application in image segmentation," Pattern Anal. Appl. 8, 332-344 (2006).
[CrossRef]

Pattern Recogn. (2)

T. Ojala and M. Pietikainen, "Unsupervised texture segmentation using feature distributions," Pattern Recogn. 32, 477-486 (1999).
[CrossRef]

E. G. P. Bovenkamp, J. Dijkstra, J. G. Bosch, and J. H. C. Reiber, "Multi-agent segmentation of IVUS images," Pattern Recogn. 37, 647-663 (2004).
[CrossRef]

Pattern Recognit. (1)

N. Pal and S. Pal, "A review on image segmentation techniques," Pattern Recognit. 26, 1277-1294 (1993).
[CrossRef]

Rev. Sci. Instrum. (1)

V. P. Maltsev, "Scanning flow cytometry for individual particle analysis," Rev. Sci. Instrum. 71, 243-255 (2000).
[CrossRef]

Vision Res. (1)

V. Navalpakkam and L. Itti, "Modeling the influence of task on attention," Vision Res. 45, 205-231 (2005).
[CrossRef]

Other (15)

P.M. Pilarski, V.J. Sieben, C. Debes Marun, and C.J. Backhouse, "An artificial intelligence system for detecting abnormal chromosomes in malignant lymphocytes," in Proceedings of Canadian Society for Immunology, Annual Conference (Halifax, Canada, 2006), pp. 126.

J.R. Taylor, An introduction to error analysis (2nd Ed., University Science Books, Sausalito, California, 1997).

R. Ghrist and D. Lipsky, "Gramatical Self Assembly for Planar Tiles," in Proceedings of International Conference on MEMS, NANO and Smart Systems, W. Badawy and W. Moussa, eds. (Banff, Alberta, 2004), pp. 205-211.

R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification (2nd Ed., Wiley Interscience, New York, 2001).

I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann, 2005).

N. Ghosh, P. Buddhiwant, A. Uppal, K. Majumder, H. S. Patel, and P. K. Gupta, "Simultaneous determination of size and refractive index of red blood cells by light scattering measurements," Appl. Phys. Lett. 88, 084101 (3 pages) (2006).
[CrossRef]

E. Duchesnay, J. J. Montois, and Y. Jacquelet, "Cooperative agents society organized as an irregular pyramid: A mammography segmentation application," Pattern Recogn. Lett. 24, 2435-2445 (2003).
[CrossRef]

M. Schmidt, "Automated Brain Tumor Segmentation," Ph.D. thesis, University of Alberta (2005).

C. Liu, C. E. Capjack, and W. Rozmus, "3-D simulation of light scattering from biological cells and cell differentiation," J. Biomed. Opt. 10, 014007 (12 pages) (2005).
[CrossRef]

L. G. Shapiro and G. C. Stockman, Computer Vision (Prentice Hall, 2001).

S. Lee and M. M. Crawford, "Unsupervised multistage image classification using hierarchical clustering with a Bayesian similarity measure," IEEE Trans. Image Process. 14, 312-320 (2005).
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C. Bourjot, V. Chevrier, and V. Thomas, "How Social Spiders Inspired an Approach to Region Detection," in Proceedings of International Conference on Autonomous Agents and MultiAgent Systems (Bologne, Italy, 2002), pp. 426-433.

D. Walther, L. Itti, M. Riesenhuber, T. Poggio, and C. Koch, "Attentional Selection for Object Recognition - a Gentle Way," in Proceedings of Biologically Motivated Computer Vision, Second International Workshop (Tubingen, Germany, 2002), pp. 472-479.

A. Sha’ashua and S. Ullman, "Structural Saliency: The Detection of Globally Salient Struc-tures Using a Locally Connected Network," in Proceedings of The International Conference on Computer Vision (Tarpon Springs, Florida, 1988), pp. 321-327.

A. P. Engelbrecht, Computational Intelligence: An Introduction (John Wiley & Sons, 2002).

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Figures (9)

Fig. 1.
Fig. 1.

Schematic diagram of a wide-angle cytometer. It includes a fluidic channel, a laser source, and a two-dimensional charge-coupled device (CCD).

Fig. 2.
Fig. 2.

Simplified example images containing features known to be present in experimental and numerically simulated scattering patterns: a series of vertical intensity bands, like those found in micro-structural scattering (left), and a number of randomly-placed highfrequency intensity regions, characteristic of nano-structural Rayleigh scattering (middle). Varying levels of high- and low- frequency intensity variation may be present in a single image, leading to complex, information-rich image structures (right). These simulated images were generated by the methods explained in the Sec. 3

Fig. 3.
Fig. 3.

(2.46 MB) Animated movie of the complete Cythe pipeline processing an example 10 pixel by 10 pixel image. Agents are represented by colored hemispheres. During the ID propagation stage of the pipeline, ID values are indicated by agent radius. The final extracted region groupings are shown by solid objects of uniform color.

Fig. 4.
Fig. 4.

Agent fixation is determined by comparing the image intensity at an agent’s position to the average intensity (µa ) within its view radius (left). After the agent_fixation() routine, members of the agent population will be fixed on areas of high intensity relative to the local image texture (right - shown here for an agent view radius of r=1). This adaptive process detects edges independent of differing background levels. Pixel color indicates 8-bit intensity, from 0 (black) to 255 (white).

Fig. 5.
Fig. 5.

An example of horizontal bridge removal (before and after removal - left and right respectively), following the agent fixation shown in Fig. 4. Green circles indicate fixed agents. Red circles represent agents that will be removed, severing the connection between the two minimally-connected bands. Numbers inside the pixels represent the ratio of horizontal to vertical neighbours within the 4-neighbourhood of a given agent (H:V).

Fig. 6.
Fig. 6.

Two parts of a single propagate_id() cycle for an active agent (center pixel). Initially, the agent surveys its local neighbourhood and records the ID values of its neighbours (left). Seeing there is a higher ID in the area (shown in red), it takes on this ID value and rebroadcasts the new ID to its neighbourhood (right). This leads to an agent neighborhood that is homogeneous with respect to the highest ID value.

Fig. 7.
Fig. 7.

A visual comparison of Cythe region detection (row B) with the initial test image (row A) for images with vertical intensity bands (left), high-frequency intensity regions (middle), and high-frequency regions overlayed onto a band structure (right, similar to those observed in FDTD simulations). Region color was assigned based on each group’s unique ID value; all regions were verified to contain distinct ID values.

Fig. 8.
Fig. 8.

A visual example of horizontal bridge removal. Left - the initial test image. Middle - the agent population directly after the agent_fixation() routine; there are three bridges at this point. Right - final region identification after post-processing; weak connections between bands did not adversely affect region identification-the two horizontal bridges were removed in the feature detection stage, and the diagonal propagation restriction prevented ID leaking over the remaining bridge (which was subsequently removed by the scrub() routine). Green dots represent fixed agents (middle), and different colors in the clustering image indicate spatially distinct regions (right).

Fig. 9.
Fig. 9.

Extraction of a band hierarchy for a simple noise-free image (top row) and for the same image with 10% of the images pixels assigned a random 8-bit intensity value (i.e. random noise; bottom row): the initial image (left), the agent population after the agent_fixation() routine (middle), and the final regions after post-processing (right). Yellow lines indicate band position (x g), and coloured regions in the post-processing image indicate spatially distinct regions g.

Tables (4)

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Table 1. The set of useful image parameters (P).

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Table 2. Statistical analysis for band intensity parameters.

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Table 3. Statistical analysis for band width parameters.

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Table 4. Statistical analysis for band number/spacing parameters.

Equations (11)

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B W b ( y ) = max x b ( y ) min x b ( y )
B W min b = min ( B W b ( y ) , y Y b )
B W max b = max ( B W b ( y ) , y Y b )
B W avg b = avg ( B W b ( y ) , y Y b )
B W dev b = 1 Y b y Y b B W b ( y ) B W avg b
B I b ( y ) = intensity ( x b , y )
B I min b = min ( B I b ( y ) , y Y b )
B I max b = max ( B I b ( y ) , y Y b )
B I avg b = avg ( B I b ( y ) , y Y b )
B I dev b = 1 Y b y Y b B I b ( y ) B I avg b
B I nn b = 1 Y b y Y b B I b ( y ) B I b ( y 1 )

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