Probabilistic tractography using Q-ball imaging and particle filtering: Application to adult and in-utero fetal brain studies

By assuming that orientation information of brain white matter fibers can be inferred from Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) measurements, tractography algorithms provide an estimation of the brain connectivity 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 framework). 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 (DWIs) are also shown to illustrate the robustness of the algorithm.

Figure optionsDownload high-quality image (53 K)Download as PowerPoint slideHighlights
► The proposed algorithm aims to provide tractographies of human brain.
► An ODF-based modeling of the diffusion is used within a particle filtering.
► The algorithm was evaluated on synthetic data and on MICCAI Fiber Cup phantom.
► Adult and fetal brain tractographies are also provided.