Tractography‐Based Automated Identification of Retinogeniculate Visual Pathway With Novel Microstructure‐Informed Supervised Contrastive Learning
Sipei Li, Wei Zhang, Shun Yao, Jianzhong He, Jingjing Gao, Tengfei Xue, Guoqiang Xie, Yuqian Chen, Erickson F Torio, Yuanjing Feng, Dhiego C A Bastos, Yogesh Rathi, Nikos Makris, Ron Kikinis, Wenya Linda Bi, Alexandra J Golby, Lauren J O'Donnell, Fan Zhang · 2024
Read Tractography‐Based Automated Identification of Retinogeniculate Visual Pathway With Novel Microstructure‐Informed Supervised Contrastive Learning by Sipei Li, Wei Zhang, Shun Yao, Jianzhong He, Jingjing Gao, Tengfei Xue, Guoqiang Xie, Yuqian Chen, Erickson F Torio, Yuanjing Feng, Dhiego C A Bastos, Yogesh Rathi, Nikos Makris, Ron Kikinis, Wenya Linda Bi, Alexandra J Golby, Lauren J O'Donnell, Fan Zhang (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11576919.txt.
Description
Sipei Li and co-authors build, in a 2024 paper, a deep learning system that finds the eye-to-brain pathway in scan data on its own. The pathway carries visual signals from the retina to a relay in the brain. Mapping it helps study vision and plan brain care. Diffusion MRI tractography can trace it in living people, but today experts pick out its fibers by hand, a slow chore with room for disagreement.
Their system, DeepRGVP, learns from both the shape of each fiber and the tissue traits along it. A contrastive method uses those tissue clues to set which fibers count as matches. A new data-boosting trick copes with the pathway's rarity among all fibers. Tests against rival systems and on fresh data check both accuracy and reach. Fast, steady mapping could aid surgery planning.
Catalog record
| CREATOR | Sipei Li, Wei Zhang, Shun Yao, Jianzhong He, Jingjing Gao, Tengfei Xue, Guoqiang Xie, Yuqian Chen, Erickson F Torio, Yuanjing Feng, Dhiego C A Bastos, Yogesh Rathi, Nikos Makris, Ron Kikinis, Wenya Linda Bi, Alexandra J Golby, Lauren J O'Donnell, Fan Zhang |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 51 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |