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http://dx.doi.org/10.9717/kmms.2012.15.12.1417

Segmentation of Neuronal Axons in Brainbow Images  

Kim, Tae-Yun (Biomedical Engineering Branch, National Cancer Center)
Kang, Mi-Sun (Department of Computer Science and Engineering, Ewha Womans University)
Kim, Myoung-Hee (Department of Computer Science and Engineering, Ewha Womans University)
Choi, Heung-Kook (Department of Computer Engineering, UHRC, Inje University)
Publication Information
Abstract
In neuroscientific research, image segmentation is one of the most important processes. The morphology of axons plays an important role for researchers seeking to understand axonal functions and connectivity. In this study, we evaluated the level set segmentation method for neuronal axons in a Brainbow confocal microscopy image. We first obtained a reconstructed image on an x-z plane. Then, for preprocessing, we also applied two methods: anisotropic diffusion filtering and bilateral filtering. Finally, we performed image segmentation using the level set method with three different approaches. The accuracy of segmentation for each case was evaluated in diverse ways. In our experiment, the combination of bilateral filtering with the level set method provided the best result. Consequently, we confirmed reasonable results with our approach; we believe that our method has great potential if successfully combined with other research findings.
Keywords
Brainbow; Confocal microscopy image; Image segmentation; Level set method; Anisotropic diffusion; Bilateral filtering;
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1 J. Livert, T.A. Weissman, H.O. Kang, R.W. Draft, J. Lu, R.A. Bennis, J.R. Sanes, and J.W. Lichtman, "Transgenic Strategies for Combinatorial Expression of Fluorsescent Proteins in the Nervous System," Nature, Vol. 450, No. 7166, pp. 56-63, 2007.   DOI   ScienceOn
2 M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active Contour Models, International Journal of Computer Vision, Kluwer Academic Publishers, Boston, 1988.
3 J.R. Beveridge, J. Griffith, R.R. Kohler, A.R. Hanson, and E.M. Riseman, Segmenting Images Using Localizing Histograms and Region Merging, International Journal of Computer Vision, Kluwer Academic Publishers, Boston,, 1989.
4 R. Adams and L. Bischof, "Seeded Region Growing," IEEE Trans Pattern Analysis Machine Intell Vo. 16, No. 6, pp. 641-647, 1994.   DOI   ScienceOn
5 R. Grzeszczuk and D. Levin, "Brownian Strings: Segmenting Images with Stochastically Deformable Contours," IEEE Trans Pattern Anal Machine Intell, Vol. 19, No. 10, pp. 1100-1114, 1997.   DOI
6 S. Lankton and A. Tannenbaum, "Localizing Region-based Active Contours," IEEE Trans Image Proc., Vol. 17, No. 11, pp. 2029-2039, 2008.   DOI   ScienceOn
7 F. Benmansour and L.D. Cohen, "Tubular Structure Segmentation Based on Minimal Path Method and Anisotropic Enhancement,: Int J . Comput Vision, Vol. 92, No. 2, pp. 192-210, 2011.   DOI
8 L.M. Lorigo, O.D. Faugeras, W.E.L. Grimson, R. Keriven, R. Kikinis, A. Nabavi, and C.F. Westin, "Curves: Curve Evolution for Vessel Segmentation," Med Image Anal, Vol. 5, No. 3, pp. 195-206, 2001.   DOI
9 D. Marín, A. Aquino, M.E. Gegundez-Arias, and J.M. Bravo, "A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants- Based Features," IEEE Trans Med Imaging, Vol. 30, No. 1, pp. 146-158, 2011.   DOI   ScienceOn
10 C.C. Reyes-Aldasoro, L.J. Williams, S. Akerman, C. Kanthou, and G.M. Tozer, "An Automatic Algorithm for the Segmentation and Morphological Analysis of Microvessels in Immunostained Histological Tumour Sections," J . Microscopy, Vol. 242, No. 3, pp. 262-278, 2011.   DOI
11 J.V.B. Soares, J.J.G. Leandro, R.M. Cesar, H.F. Jelinek, and M.J. Cree, "Retinal Vessel Segmentation Using the 2-D Gabor Wavelet and Supervised Classification," IEEE Trans Med Imaging, Vol. 25, No. 9, pp. 1214-1222, 2006.   DOI
12 Y. Zhang, K. Chen, M. Baron, M.A. Teylan, Y. Kim, Z. Song, P. Greengard, and S.T.C. Wong, "A Neurocomputational Method for Fully Automated 3D Dendritic Spine Detection and Segmentation of Medium-Sized Spiny Neurons," NeuroImage, Vol. 50, No. 4, pp. 1472-1484, 2010.   DOI
13 H. Cai, X. Xu, J. Lu, J.W. Lichtman, S.P. Yung, and S.T.C. Wong, "Repulsive Force Based Snake Model to Segment and Track Neuronal Axons in 3D Microscopy Image Stacks," NeuroImage Vol. 32, No. 4, pp. 1608-1620, 2006.   DOI
14 R. Srinivasan, X. Zhou, E. Miller, J. Lu, J. Lichtman, and S.T.C. Wong, "Automated Axon Tracking of 3D Confocal Laser Scanning Microscopy Images Using Guided Probabilistic Region Merging," Neuroinformatics, Vol. 5, No. 3, pp. 189-203, 2007.   DOI
15 A.R. Cohen, B. Roysam, and J.N. Turner, "Automated Tracing and Volume Measurements of Neurons from 3-D Confocal Fluorescence Microscopy Data," J . Microscopy, Vol. 173, No. 2, pp. 103-114, 1994.   DOI
16 J. Wang, X. Zhou, J. Lu, J. Lichtman, S.F. Chang, and S.T.C. Wong, "Dynamic Local Tracing for 3D Aaon Curvilinear Structure Detection from Microscopic Image Stacks," Proc. 4th IEEE Int Symposium Biomed Imaging: From Nano to Macro, pp. 81-84, 2007.
17 A. Vasilevskiy and K. Siddiqi, "Flux Maximizing Geometric Flows," IEEE Trans Pattern Anal Machine Intell, Vol. 24, No. 12, pp. 1565-1578, 2002.   DOI
18 J. Sethian, "A Fast Marching Level Set Method for Monotonically Advancing Fronts," PNAS, Vol. 93, No. 4, pp. 1591-1595, 1996.   DOI
19 V. Caselles, F. Catte, T. Coll, and F. Dibos, "A Geometric Model for Active Contours in Image Processing," Numerische Math, Vol. 66, No. 1, pp. 1-31, 1993.   DOI   ScienceOn
20 O. Gloger, K.D. Tonnies, V. Liebscher, B. Kugelmann, R. Laqua, and H. Volzke, "Prior Shape Level Set Segmentation on Multistep Generated Probability Maps of MR Datasets for Fully Automatic Kidney Parenchyma Volumetry," IEEE Trans Med Imaging, Vol. 31, No. 2, pp. 312-325, 2012.   DOI
21 L.A. Vese and T.F. Chan, "A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model," Int J Computer Vision, Vol. 50, No. 3, pp. 271- 293, 2002.   DOI
22 C. Li, C. Xu, C.F. Gui, and M.D. Fox, "Level Set Evolution without Re-initialization: A New Variational Formulation," Proc. IEEE Comput Soc Conf Comput Vision Pattern Recog (CVPR'05), Vol. 1, pp. 430-436, 2005.
23 S. Grgic, M. Grgic, and M. Mrak, "Reliability of Objective Picture Quality Measures," J Elect Eng, Vol. 55, No. 55, pp. 3-10, 2004.
24 J.P. Lewis, "Fast Template Matching," Proc. Canadian Image Process Pattern Recog Soc Vision Interface, pp. 120-123, 1995.
25 M. Miyahara, K. Kotani, and V.R. Algazi, "Objective Picture Quality Scale (PQS) for Image Coding," IEEE Trans Commun, Vol. 46, No. 9, pp. 1215-1226, 1998.   DOI
26 Y.M. Choi and M.W. Choo, "Comparison of Feature Selection Processes for Image Retrieval Applications, "J ournal of Korea Multimedia Society, Vol. 14, No. 12, pp. 1544-1548, 2011.   과학기술학회마을   DOI
27 A. Vazquez-Reina, E. Miller, and H. Pfister, "Multiphase Geometric Coupling for the Segmentation of Neural Processes," Proc. IEEE Comput Soc Conf Comput Vision Pattern Recog (CVPR2009), pp. 2020-2027, 2009.
28 H.J. Choi, I.H. Choi, T.Y. Kim, N.H. Cho, and H.K. Choi, "Three-dimensional Visualization and Quantitative Analysis of Cervical Cell Nuclei with Confocal Laser Scanning Microscopy," Anal Quant Cytol Histol, Vol. 27, No. 3, pp. 174-180, 2005.
29 T.Y. Kim, H.J. Choi, H.G. Hwang, and H.K. Choi, "Three-dimensional Texture Analysis of Renal Cell Carcinoma Cell Nuclei for Computerized Automatic Grading," J . Med Syst, Vol. 34, No. 4, pp. 709-716, 2010.   DOI
30 D. Nain, A.J. Yezzi, and G. Turk G, "Vessel Segmentation Using a Shape Driven Flow," Proc. Med Image Comput Computer Assisted Intervention pp. 51-59, 2004.
31 W.K. Jeong, J. Beyer, M. Hadwiger, A. Vazquez, H. Pfister, and R.T. Whitaker RT, "Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets," IEEE Trans Visual Comput Graph, Vol. 15, No. 1, pp. 1505-1514, 2009.   DOI
32 E. Jurrus, M. Hardy, T. Tasdizen, P.T. Fletcher, P. Kpshevoy, C.B. Chien, W. Denk, and R. Whitaker, "Axon Tracking in Serial Block- face Scanning Electron Microscopy," Med Image Anal, Vol. 13, No. 1, pp. 180-188, 2009.   DOI
33 F. Liu and J. Liu, "Anisotropic Diffusion for Image Denoising based on Diffusion Tensors," J Vis Comm. and Image Rep., Vol. 23, No. 3, pp. 516-521, 2012.   DOI
34 P. Perona and J. Malik, "Scale-space and Edge Detection Using Anisotropic Diffusion," IEEE Trans Pattern Anal Machine Intell, Vol. 12, No. 7, pp. 629-639, 1990.   DOI   ScienceOn
35 D. Barash , "Bilateral Filtering and Anisotropic Diffusion: Towards a Unified Viewpoint," Lecture Notes Comput Sci 2006, pp. 273-280, 2006.
36 F. Hofheinz, J. Langner, B. Beuthien-Baumann, L. Oehme, J. Steinbach, J. Kotzerke, and J. van den Hoff, "Suitability of Bilateral Filtering for Edge-preserving Noise Reduction in PET," EJNMMI Research, Vol. 1, No. 1, pp. 1-9, 2011.   DOI
37 C. Tomaci and R. Mabduchi, "Bilateral Filtering for Gray and Color Images," Proc. 6th IEEE Int Conf Comput Vision, pp. 839-846, 1998.