Locally-constrained region-based methods for DW-MRI segmentation

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2007, Pages

  Melonakos, John ^a   Kubicki, Marek ^b   Niethammer, Marc ^b   Miller, James V ^c   Mohan, Vandana ^a   Tannenbaum, Allen ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c GE GLOBAL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FIBER BUNDLES;

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS; COMPUTER VISION; IMAGE PROCESSING; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; RESONANCE;

COMPUTATIONAL METHODS;

EID: 50649118604     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2007.4409167     Document Type: Conference Paper

References (34)

1. D. Alexander, J. Gee, and R. Bajcsy. Similarity measures for matching diffusion tensor images. In Proceedings of the British Machine Vision Conference (BMVC), 1999.
2. P. Basser, S. Pajevic, C. Pierpaoli, J. Duda, and A. Aldroubi. In vivo fiber tractography using DT-MRI data. Magnetic Resonance in Medicine, 44(4):625-632, 2000.
3. P. Basser and C. Pierpaoli. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B, 111(3):209-219, 1996.
4. T. Chan and L. Vese. Active contours without edges. Image Processing, IEEE Transactions on, 10(2):266-277, 2001.
5. T. Conturo, N. Lori, T. Cull, E. Akbudak, A. Snyder, J. Shimony, R. McKinstry, H. Burton, and M. Raichle. Tracking neuronal fiber pathways in the living human brain. Proc Natl Acad Sci US A, 96(18):10422-10427, 1999.
6. T. Fletcher, R. Tao, W. Jeong, and R. Whitaker. A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor MRI. IPMI, 2007.
7. O. Friman, G. Farnebäck, and C. Westin. A Bayesian approach for stochastic white matter tractography. IEEE Transactions on Medical Imaging, 25(8):965, 2006.
8. M. Jackowski, C. Kao, M. Qiu, R. Constable, and L. Staib. White matter tractography by anisotropic wavefront evolution and diffusion tensors imaging. Medical Image Analysis, 9:427-440, 2005.
9. L. Jonasson, X. Bresson, P. Hagmann, O. Cuisenaire, R. Meuli, and J. Thiran. White matter fiber tract segmentation in DT-MRI using geometric flows. Medical Image Analysis, 9(3):223-236, 2005.
10. L. Jonasson, P. Hagmann, C. Pollo, X. Bresson, C. Wilson, R. Meuli, and J. Thiran. A level set method for segmentation of the thalamus and its nuclei in DT-MRI. Signal Processing, 87(2):309-321, 2007.
11. C. Kao, S. Osher, and J. Qian. Lax-Friedrichs sweeping scheme for static Hamilton-Jacobi equations. Journal of Computational Physics, 196(1):367-391, 2004.
12. C. Kao, S. Osher, and Y. Tsai. Fast sweeping methods for static Hamilton-Jacobi equations. SIAM journal on numerical analysis, 42(6):2612-2632, 2005.
13. M. Kubicki, C. Westin, P. Nestor, C. Wible, M. Frumin, S. Maier, R. Kikinis, F. Jolesz, R. McCarley, and M. Shenton. Cingulate fasciculus integrity disruption in schizophrenia: a magnetic resonance diffusion tensor imaging study. Biological Psychiatry, 54(11):1171-1180, 2003.
14. C. Lenglet, M. Rousson, and R. Deriche. DTI segmentation by statistical surface evolution. IEEE Transactions on Medical Imaging, 25(6):685-700, 2006.
15. C. Lenglet, M. Rousson, R. Deriche, O. Faugeras, S. Lehericy, and K. Ugurbil. A Riemannian Approach to Diffusion Tensor Images Segmentation. Proceedings of the 19th International Conference on Information Processing in Medical Imaging (IPMI), Glenwood Springs, CO, USA, pages 591-602, 2005.
16. J. Melonakos, V. Mohan, M. Niethammer, K. Smith, M. Kubicki, and A. Tannenbaum. Finsler tractography for white matter connectivity analysis of the cingulum bundle. MICCAI, 2007. to appear.
17. J. Melonakos, E. Pichon, S. Angenent, and A. Tannenbaum. Finsler active contours. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007. in press.
18. B. Moberts, A. Vilanova, and J. van Wijk. Evaluation of Fiber Clustering Methods for Diffusion Tensor Imaging. Visualization, IEEE 2005, pages 9-9, 2005.
19. S. Mori, B. Crain, V. Chacko, and P. van Zijl. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol, 45(2):265-9, 1999.
20. S. Mori and P. van Zijl. Fiber tracking: principles and strategies- a technical review. NMR in Biomedicine, 15(7-8):468-480, 2002.
21. D. Mumford. Bayesian rationale for energy functionals. In Geometry-driven diffusion in Computer Vision, pages 141-153. 1994.
22. L. O'Donnell. Cerebral white matter analysis using diffusion imaging. 2006.
23. L. ODonnell, S. Haker, and C. Westin. New Approaches to Estimation of White Matter Connectivity in Diffusion Tensor MRI: Elliptic PDEs and Geodesics in a Tensor-Warped Space. Computing and Computer Assisted Intervention, LNCS, 2488:459-466, 2002.
24. G. Parker, H. Haroon, and C. Wheeler-Kingshott. A framework for a streamline-based probabilistic index of connectivity(PICo) using a structural interpretation of MRI diffusion measurements. Journal of Magnetic Resonance Imaging, 18(2):242-254, 2003.
25. G. Parker, C. Wheeler-Kingshott, and G. Barker. Estimating distributed anatomical connectivity using fast marching-methods and diffusion tensor imaging. Medical Imaging, IEEE Transactions on, 21(5):505-512, 2002.
26. M. Perrin, C. Poupon, Y. Cointepas, B. Rieul, N. Golestani, C. Pallier, D. Riviere, A. Constantinesco, and D. Le Bihan. Fiber tracking in Q-ball fields using regularized particle trajectories. Proc. of IPMI, 2(3), 2005.
27. E. Pichon. Novel methods for multidimensional image segmentation. PhD thesis, Georgia Institute of Technology, 2005.
28. E. Pichon, C. Westin, and A. Tannenbaum. A Hamilton-Jacobi-Bellman approach to high angular resolution diffusion tractography. Eighth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI05). Lecture Notes in Computer Science, 3749:180-187.
29. E. Prados, C. Lenglet, J. Pons, N. Wotawa, R. Deriche, O. Faugeras, and S. Soatto. Control Theory and Fast Marching Techniques for Brain Connectivity Mapping. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Volume 1, pages 1076-1083, 2006.
30. Y. Rathi, O. Michailovich, J. Malcolm, and A. Tannenbaum. Seeing the unseen: Segmenting with distributions. In Intl. Conf. Signal and Image Processing, 2006.
31. M. Rousson, C. Lenglet, and R. Deriche. Level Set and Region Based Surface Propagation for Diffusion Tensor MRI Segmentation. Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis, 3(5):36, 2004.
32. J. Schmahmann and D. Pandya. Fiber Pathways of the Brain. Oxford University Press, 2006.
33. B. Stieltjes, W. Kaufmann, P. van Zijl, K. Fredericksen, G. Pearlson, M. Solaiyappan, and S. Mori. Diffusion Tensor Imaging and Axonal Tracking in the Human Brainstem. NeuroImage, 14(3):723-735, 2001.
34. F. Wang, Z. Sun, L. Cui, X. Du, X. Wang, H. Zhang, Z. Cong, N. Hong, and D. Zhang. Anterior Cingulum Abnormalities in Male Patients With Schizophrenia Determined Through Diffusion Tensor Imaging, 2004.