Interactive segmentation with Intelligent Scissors
Graphical Models and Image Processing
Adaptive Kernels for Multi-fiber Reconstruction
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
A Novel Global Tractography Algorithm Based on an Adaptive Spin Glass Model
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
ODF reconstruction in Q-ball imaging with solid angle consideration
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
SMT: split and merge tractography for DT-MRI
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Approximating Symmetric Positive Semidefinite Tensors of Even Order
SIAM Journal on Imaging Sciences
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Information on the directionality and structure of axonal fibres in neural tissue can be obtained by analysing diffusion-weighted MRI data sets. Several fibre tracking algorithms have been presented in the literature that trace the underlying field of principal orientations of water diffusion, which correspond to the local primary eigenvectors of the diffusion tensor field. However, the majority of the existing techniques ignore the secondary and tertiary orientations of diffusion, which contain significant information on the local patterns of diffusion. In this paper, we introduce the idea of perpendicular fibre tracking and present a novel dynamic programming method that traces surfaces, which are locally perpendicular to the axonal fibres. This is achieved by using a cost function, with geometric and fibre orientation constraints, that is evaluated dynamically for every voxel in the image domain starting from a given seed point. The proposed method is tested using synthetic and real DW-MRI data sets. The results conclusively demonstrate the accuracy and effectiveness of our method.