IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic clustering and quantitative analysis of white matter fiber tracts
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Multi-fiber reconstruction from diffusion MRI using mixture of wisharts and sparse deconvolution
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Probabilistic fiber tracking using particle filtering
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
IEEE Transactions on Image Processing
Information Theoretic Methods for Diffusion-Weighted MRI Analysis
Emerging Trends in Visual Computing
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
International Journal of Computer Vision
Accelerated diffusion operators for enhancing DW-MRI
EG VCBM'10 Proceedings of the 2nd Eurographics conference on Visual Computing for Biology and Medicine
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In this paper we present a novel method for estimating a field of asymmetric spherical functions, dubbed tractosemas, given the intra-voxel displacement probability information. The peaks of tractosemas correspond to directions of distinct fibers, which can have either symmetric or asymmetric local fiber structure. This is in contrast to the existing methods that estimate fiber orientation distributions which are naturally symmetric and therefore cannot model asymmetries such as splaying fibers. We propose a method for extracting tractosemas from a given field of displacement probability iso-surfaces via a diffusion process. The diffusion is performed by minimizing a kernel convolution integral, which leads to an update formula expressed in the convenient form of a discrete kernel convolution. The kernel expresses the probability of diffusion between two neighboring spherical functions and we model it by the product of Gaussian and von Mises distributions. The model is validated via experiments on synthetic and real diffusion-weighted magnetic resonance (DW-MRI) datasets from a rat hippocampus and spinal cord.