Suyash P. Awate
research & publications
CV / resume
personal
 
DTI Segmentation
Fiber Bundle Segmentation
Cingulum Segmentation
 
Suyash P. Awate, Hui Zhang , James C. Gee
A Fuzzy, Nonparametric Segmentation Framework for DTI and MRI Analysis: With Applications to DTI-Tract Extraction
IEEE Trans. Med. Imaging 2007, 26(11):1525-1536
 
Suyash P. Awate, James C. Gee
A Fuzzy, Nonparametric Segmentation Framework for DTI and MRI Analysis
Proc. Information Processing in Medical Imaging 2007, Springer LNCS 4584 pp. 296-307
 
Challenges using Streamline Tractography to Extract Cingulum
dashed-line = ground truth
(1) streamlines terminate before the bend
dti segmentation, fiber bundle, cingulum
(2) streamlines leak out of the cingulum
dti segmentation, fiber bundle, cingulum
 
Modeling Statistics of Tensors in Fiber Bundles
tensors in fiber bundles can lie on arbitrary hyper-surfaces in the Riemannian space of diffusion tensors (i.e. SPD matrices)
dti segmentation, fiber bundle, cingulum
 
We infer the probability density function of the tensors via kernel density estimation in the Riemannian space
 
The density estimates can be shown to converge by combining results from the (i) Log-Euclidean framework [Arsigny et al.] and (ii) kernel density estimation [Pelletier et al.]
 
Segmentation Results
initialize via (i) probabilistic atlas (3D) or (ii) manually (one slice suffices)
dti segmentation, fiber bundle, cingulum
dti segmentation, fiber bundle, cingulum
 
Comparing Tractography and Segmentation
(1) streamline tractography
dti segmentation, fiber bundle, cingulum
(2) segmentation
dti segmentation, fiber bundle, cingulum
 
Related Work
 
L. Concha, D. Gross, C. Beulieu
Diffusion tensor tractography of the limbic system
Amer. J. Neuroradiology 2005, 26:2267-2274
 
Gong, Jiang, Zhu, Zang, Wang, Xie, Xiao, and Guo
Asymmetry analysis of cingulum based on scale-invariant parameterization by diffusion
tensor imaging
Human Brain Mapping 2005, 24:92-98
 
C. Lenglet, M. Rousson, R. Deriche, O. Faugeras, S. Lehericy, and K. Ugurbil
A Riemannian approach to diffusion tensor image segmentation
Proc. Information Processing in Medical Imaging 2005, pp. 591-602
 
Z. Wang, B. Vemuri
DTI segmentation using an information-theoretic tensor dissimilarity measure
IEEE Trans. Medical Imaging 2005, 24(10):1267-1277
 
B. Pelletier
Kernel density estimation on Riemannian manifolds
Stat. and Prob. Letters 2005, 73:297-304
 
V. Arsigny, P. Fillard, X. Pennec, N. Ayache
Geometric means in a novel vector space structure on symmetric positive-definite matrices
SIAM J. Matrix Analysis and Applications 2007, 29(1):328-347