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Updated: Jul 16, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Think deep in the tractography game: deep learning for tractography computing and analysis
Fan Zhang1, Antoine Théberge2, Pierre-Marc Jodoin2
1University of Electronic Science and Technology of China, Chengdu, China. fan.zhang@uestc.edu.cn.
Abstract:
Tractography is a challenging process with complex rules, driving continuous algorithmic evolution to address its challenges. Meanwhile, deep learning has tackled similarly difficult tasks, such as mastering the Go board game and animating sophisticated robots. Given its transformative impact in these areas, deep learning has the potential to revolutionize tractography within the framework of existing rules. This work provides a brief summary of recent advances and challenges in deep learning-based tractography computing and analysis.

