Using nonlinear diffusion and mean shift to detect and connect cross-sections of axons in 3D optical microscopy images

Medical Image Analysis

Volumn 12, Issue 6, 2008, Pages 666-675

  Cai, Hongmin ^a   Xu, Xiaoyin ^b   Lu, Ju ^c   Lichtman, Jeff ^c   Yung, S P ^a   Wong, Stephen T C ^d  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

^c HARVARD UNIVERSITY   (United States)

^d WEILL CORNELL MEDICAL COLLEGE   (United States)

Author keywords

Image analysis; Mean shift; Neuronal image processing; Nonlinear diffusion; Optical microscopy; Segmentation

Indexed keywords

CONFOCAL MICROSCOPY; DATA PROCESSING; DIFFUSION; IMAGE ANALYSIS; IMAGE ENHANCEMENT; IMAGE PROCESSING; MATHEMATICAL MORPHOLOGY; MICROSCOPIC EXAMINATION; NETWORK PROTOCOLS; NEUROLOGY; NEURONS; OPTICAL DATA PROCESSING; OPTICAL DATA STORAGE; OPTICAL INSTRUMENTS; OPTICAL MICROSCOPY; SEMICONDUCTOR DOPING; SENSOR NETWORKS; VECTOR QUANTIZATION;

2D IMAGES; 3D MORPHOLOGIES; CONFOCAL LASER SCANNING MICROSCOPIES; HIGH-RESOLUTION; LABELING TECHNIQUES; MEAN SHIFT; MEAN SHIFTS; MORPHOLOGICAL OPERATIONS; NEURONAL IMAGE PROCESSING; NEURONAL NETWORKS; NONLINEAR DIFFUSION; NONLINEAR DIFFUSIONS; OPTICAL MICROSCOPES; REAL DATUM; REMOVE NOISES; SEGMENTATION; SPLIT AND MERGES; THREE DIMENSIONS; THREE STEPS;

THREE DIMENSIONAL;

ANIMAL TISSUE; ARTICLE; CONFOCAL LASER MICROSCOPY; CONTROLLED STUDY; DIFFUSION; IMAGE PROCESSING; IMAGE RECONSTRUCTION; MOUSE; NERVE FIBER; NOISE REDUCTION; NONHUMAN; NONLINEAR SYSTEM; PERFORMANCE; PRIORITY JOURNAL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ANATOMY, CROSS-SECTIONAL; ANIMALS; ARTIFICIAL INTELLIGENCE; AXONS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MICE; MICE, TRANSGENIC; MICROSCOPY; PATTERN RECOGNITION, AUTOMATED; PERIPHERAL NERVES; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 54249159267     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.media.2008.03.002     Document Type: Article

References (51)

1. Al-Kofahi K., Lasek S., Szarowski D., Pace C., Nagy G., Turner J., and Roysam B. Rapid automated three-dimensional tracing of neurons from confocal image stacks. IEEE Trans. Info. Tech. Biomed. 6 2 (2002) 171-187
2. Aylward S., and Bullitt E. Initialization, noise, singularities and scale in height ridge traversal for tubular object centerline extraction. IEEE Trans. Med. Imag. 21 2 (2002) 61-75
3. Aylward, S., Pizer, S., Bullitt, E., Eberl, D., 1996. Intensity ridge and widths for tabular object segmentation and registration. In: IEEE Workshop Math. Methods in Biomed. Image Analysis, pp. 131-138.
4. Cai H., Xu X., Lu J., Lichtman J., Yung S., and Wong S. Repulsive force based snake model to segment and track neuronal axons in 3D microscopy image stacks. NeuroImage 32 4 (2006) 1608-1620
5. Can A., Shen H., Turner J., Tanenbaum H., and Roysam B. Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms. IEEE Trans. Info. Tech. Biomed. 3 2 (1999) 125-138
6. Carmona R., and Zhong S. Adaptive smoothing respecting feature directions. IEEE Trans. Image Proc. 7 3 (1998) 353-358
7. Catte F., Lions P.-L., Morel J.-M., and Coll T. Image selective smoothing and edge detection by nonlinear diffusion. SIAM J. Numer. Anal. 29 1 (1992) 182-193
8. Chalfie M., Tu Y., Euskirchen G., Ward W., and Prasher D. Green fluorescent protein as a marker for gene expression. Science 263 (1994) 802-805
9. Chan T., Shen J., and Vese L. Variational PDE models in image processing. Notice Am. Math. Soc. 50 (2003) 14-26
10. Cheng Y. Mean shift, mode seeking and clustering. IEEE Trans. Pattern Anal. Machine Intell. 17 8 (1995) 790-799
11. Collins R. Mean-shift blob tracking through scale space. IEEE Computer Society Conference on Computer Vision and Pattern Recognition vol. 2 (2003), IEEE Press 234-240
12. Comaniciu D., and Meer P. Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Machine Intell. 24 5 (2002) 603-619
13. Debeir O., Van Ham P., Kiss R., and Decaestecker C. Tracking of migrating cells under phase-contrast video microscopy with combined mean-shift processes. IEEE Trans. Med. Imag. 24 6 (2005) 697-711
14. Dong, G., Acton, S., 2003. A variational method for leukocyte detection. In: IEEE International Conference on Image Proc. (ICIP), pp. II: 161-164.
15. Feng G., Mellor R., Bernstein M., Keller-Peck C., Nguyen Q., Wallace M., Nerbonne J., Lichtman J., and Sanes J. Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron 28 1 (2000) 41-51
16. Fukunaga K., and Hostetler L. The estimation of the gradient of a density function, with applications in pattern recognition. IEEE Trans. Inform. Theory 21 1 (1975) 32-40
17. Gilboa, G., Zeevi, Y., Sochen, N., 2001. Image enhancement segmentation and denoising by time dependent nonlinear diffusion processes. In: IEEE Int. Conf. Image Proc. (ICIP), pp. 134-137.
18. Hadjidemetriou, S., Toomre, D., Duncan, J.S., 2005. Segmentation and 3D Reconstruction of Microtubules in Total Internal Reflection Fluorescence Microscopy (TIRFM). In: 8th Med Image Comput Comput Assist Interv (MICCAI) Int. Conf. Med. Image Computing and Computer Asst. Intervention, pp. 761-769.
19. Jiang M., Ji Q., and McEwen B.F. Automated extraction of fine features of kinetochore microtubules and plus-ends from electron tomography volume. IEEE Trans. Image Process. 15 7 (2006) 2035-2048
20. Kass M., Witkin A., and Terzopoulos D. Snakes: active contour models. Int. J. Comput. Vis. 1 (1987) 321-332
21. Kasthuri N., and Lichtman J. The role of neuronal identity in synaptic competition. Nature 424 6947 (2003) 426-430
22. Koepfler G., Lopez C., and Morel J.M. A multiscale algorithm for image segmentation by variational method. SIAM J. Numer. Anal. 31 1 (1994) 282-299
23. Krim, H., Bao, Y., 1999. Nonlinear diffusion: a probabilistic view. In: IEEE Int. Conf. Image Proc. (ICIP), vol. 2, pp. 21-25.
24. Krissian D., Malandain G., Ayache N., Vaillant R., and Trousset Y. Model-based detection of tubular structures in 3D images. Comp. Vis. Image Understand. 80 2 (2000) 130-171
25. Lysaker M., Lundervold A., and Tai X. Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time. IEEE Trans. Image Proc. 12 12 (2003) 1579-1590
26. Malladi R., Sethian J., and Vemuri B. Shape modeling with front propagation: a level set approach. IEEE Trans. Pattern Anal. Machine Intell. 17 (1995) 158-175
27. Marquina A., and Mulet P. High-order total variation-based image restoration. SIAM J. Sci. Comput. 22 (2000) 503-516
28. Meijering E., Jacob M., Sarria J.-C., Steiner P., Hirling H., and Unser M. Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images. Cytometry Part A 58A 2 (2004) 167-176
29. Moisan L., Guichard F., and Morel J. A review of p.d.e. models in image processing and image analysis. J. Phys. IV 12 (2002) 137-154
30. Mukherjee D., Ray N., and Acton S. Level set analysis for leukocyte detection and tracking. IEEE Trans. Image Process. 13 4 (2004) 562-572
31. Niessen, W., ter Haar Romeny, B., Florack, L., Salden, A., 1994. Nonlinear diffusion of scalar images using well-posed differential operators with applications in medical imaging. In: IEEE Computer Vision and Pattern Recognition, pp. 92-97.
32. Osher S., and Fedkiw R.P. Level set methods: an overview and some recent results. J. Comput. Phys. 169 2 (2001) 463-502
33. Perona P., and Malik J. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Machine Intell. 12 7 (1990) 629-638
34. Quek F., and Kirbas C. Vessel extraction in medical images by wave-propagation and traceback. IEEE Trans. Med. Imag. 20 2 (2001) 117-131
35. Ray N., and Acton S. Motion gradient vector flow: an external force for tracking rolling leukocytes with shape and size constrained active contours. IEEE Trans. Med. Imag. 23 12 (2004) 1466-1478
36. Ray N., Acton S., and Ley K. Tracking leukocytes in vivo with shape and size constrained active contours. IEEE Trans. Med. Imag. 21 10 (2002) 1222-1235
37. Rudin L., Osher S., and Fatemi E. Nonlinear total variation based noise removal algorithms. Physica D 60 (1992) 259-268
38. Saban, M., Altinok, A., Peck, A., Kenney, C., Feinstein, S., Wilson, L., Rose, K., Manjunath, B.S., 2006. Automated tracking and modeling of microtubule dynamics. In: IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1032-1035.
39. Sanes J., and Lichtman J. Development of the vertebrate neuromuscular junction. Annu. Rev. Neurosci. 22 (1999) 389-442
40. Sato Y., Nakajima S., Shiraga N., Atsumi H., Yoshida S., Koller T., Gerig G., and Kikinis R. Three dimensional multiscale line filter for segmentation and visualization of curvilinear strutures in medical images. Med. Image Anal. 2 2 (1998) 143-168
41. Serra J. Image Analysis and Mathematical Morphology: Theoretical Advances (1989), Academic Press, London
42. Sethian J. A fast marching level set method for monotonically advancing fronts. Proc. Natl. Acad. Sci. 93 4 (1996) 1591-1595
43. Srinivasan R., Zhou X., Miller E., Lu J., Lichtman J., and Wong S. Automated axon tracking of 3D confocal laser scanning microscopy images using guided probabilistic region merging. Neuroinformatics 5 3 (2007) 189-203
44. Tsai C.-L., Stewart C., Tanenbaum H., and Roysam B. Model-based method for improving the accuracy and repeatability of estimating vascular bifurcations and crossovers from retinal fundus images. IEEE Trans. Info. Tech. Biomed. 8 2 (2004) 122-130
45. Wang, J., Thiesson, B., Xu, Y., Cohen, M., 2004. Image and video segmentation by anisotropic kernel mean shift. In: Proceedings of the 8th European Conference on Computer Vision, pp. 238-249.
46. Weickert J. Coherence-enhancing diffusion filtering. Adjunct. Pyramids Curve Evol. Scale-Spaces 31 2/3 (1999) 111-127
47. Weickert J. Applications of nonlinear diffusion in image processing and computer vision. Acta Math. Univ. Comenianae LXX 1 (2001) 33-50
48. Weickert J., and Schnorr C. PDE-based preprocessing of medical images. Knstliche Intelligenz 3 (2000) 5-10
49. Yilmaz, A., Shafique, K., Lobo, N., Lin, X., Olson, T., Shah, M., 2001. Target tracking in FLIR imagery using mean-shift and global motion compensation. In: IEEE Workshop on Computer Vision Beyond the Visible Spectrum, pp. 54-58.
50. You Y., and Kaveh M. Fourth-order partial differential equations for noise removal. IEEE Trans. Image Proc. 9 10 (2000) 1723-1730
51. Zimmer C., Labruyere E., Meas-Yedid V., Guillen N., and Olivo-Marin J.-C. Segmentation and tracking of migrating cells in videomicroscopy with parametric active contours: a tool for cell-based drug testing. IEEE Trans. Med. Imag. 21 10 (2002) 1212-1221