Probabilistic Tractography Using Q-Ball Imaging and Particle Filtering: Application to Adult and in-utero Fetal Brain Studies

Julien Pontabry (1) , François Rousseau (2) , Estanislao Oubel (1) , Colin Studholme (3) , Mériam Koob (4, 5) , Jean-Louis Dietemann (5)

1 LSIIT
2 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
3 BICG, Dept. of Pediatrics
4 Service de Radiologie
5 Service de radiologie [Strasbourg]

By assuming that orientation information of brain white matter fibers can be inferred from Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) mea- surements, tractography algorithms provide an estimation of the brain connec- tivity in-vivo. The two key ingredients of tractography are the diffusion model (tensor, high-order tensor, Q-ball, etc.) and the means to deal with uncertainty during the tracking process (deterministic vs probabilistic mathematical frame- work). In this paper, we investigate the use of an analytical Q-ball model for the diffusion data within a well-formalized particle filtering framework. The proposed method is validated and compared to other tracking algorithms on the MICCAI'09 contest Fiber Cup phantom. Tractographies of in-vivo adult and fetal brain Diffusion-Weighted Images (DWI) are also shown to illustrate the robustness of the algorithm.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Julien Pontabry, François Rousseau, Estanislao Oubel, Colin Studholme, Mériam Koob, et al.. Probabilistic Tractography Using Q-Ball Imaging and Particle Filtering: Application to Adult and in-utero Fetal Brain Studies. Medical Image Analysis, 2012, 17, pp.297-310. ⟨10.1016/j.media.2012.11.004⟩. ⟨hal-00873625⟩