Trace Inference, Curvature Consistency, and Curve Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Orthonormal Vector Sets Regularization with PDE's and Applications
International Journal of Computer Vision
A Regularization Scheme for Diffusion Tensor Magnetic Resonance Images
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
A Spin Glass Based Framework to Untangle Fiber Crossing in MR Diffusion Based Tracking
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Diffusion MRI Tractography of Crossing Fibers by Cone-Beam ODF Regularization
Proceedings of the 31st DAGM Symposium on Pattern Recognition
An improved representation of junctions through asymmetric tensor diffusion
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
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We develop a differential geometric framework for regularizing diffusion MRI data. The key idea is to model white matter fibers as 3D space curves and to then extend Parent and Zucker’s 2D curve inference approach [8] by using a notion of co-helicity to indicate compatibility between fibre orientation estimates at each voxel with those in a local neighborhood. We argue that this provides several advantages over earlier regularization methods. We validate the approach quantitatively on a biological phantom and on synthetic data, and qualitatively on data acquired in vivo from a human brain.