Segmentation of Short Association Bundles in Massive Tractography Datasets Using a Multi-subject Bundle Atlas

This paper presents a method for automatic segmentation of some short association fiber bundles from massive dMRI tractography datasets. The method is based on a multi-subject bundle atlas derived from a two-level intra-subject and inter-subject clustering strategy. Each atlas bundle corresponds to one or more inter-subject clusters, presenting similar shapes. An atlas bundle is represented by the multi-subject list of the centroids of all intra-subject clusters in order to get a good sampling of the shape and localization variability. An atlas of 47 bundles is inferred from a first database of 12 brains, and used to segment the same bundles in a second database of 10 brains.

[1]  Maxime Descoteaux,et al.  Inference of a HARDI Fiber Bundle Atlas Using a Two-Level Clustering Strategy , 2010, MICCAI.

[2]  M. Catani,et al.  A diffusion tensor imaging tractography atlas for virtual in vivo dissections , 2008, Cortex.

[3]  W. Eric L. Grimson,et al.  Tractography segmentation using a hierarchical Dirichlet processes mixture model , 2011, NeuroImage.

[4]  Sung Yong Shin,et al.  Spectral-based automatic labeling and refining of human cortical sulcal curves using expert-provided examples , 2010, NeuroImage.

[5]  Alan Connelly,et al.  Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution , 2007, NeuroImage.

[6]  Maxime Descoteaux,et al.  Robust clustering of massive tractography datasets , 2011, NeuroImage.

[7]  Carl-Fredrik Westin,et al.  Automatic Tractography Segmentation Using a High-Dimensional White Matter Atlas , 2007, IEEE Transactions on Medical Imaging.

[8]  Nassir Navab,et al.  Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010, 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part III , 2010, MICCAI.

[9]  Susumu Mori,et al.  Fiber tracking: principles and strategies – a technical review , 2002, NMR in biomedicine.

[10]  Jan K. Buitelaar,et al.  Partition-based mass clustering of tractography streamlines , 2011, NeuroImage.

[11]  Arthur W. Toga,et al.  Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy , 2010, NeuroImage.

[12]  R. Deriche,et al.  Regularized, fast, and robust analytical Q‐ball imaging , 2007, Magnetic resonance in medicine.

[13]  Alain Trouvé,et al.  Diffeomorphic Brain Registration Under Exhaustive Sulcal Constraints , 2011, IEEE Transactions on Medical Imaging.

[14]  C. Westin,et al.  A method for clustering white matter fiber tracts. , 2006, AJNR. American journal of neuroradiology.

[15]  Arthur W. Toga,et al.  Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter , 2008, NeuroImage.

[16]  Guido Gerig,et al.  Towards a shape model of white matter fiber bundles using diffusion tensor MRI , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).