Conference paper
New insights from the IronTract challenge: Simple post-processing enhances the accuracy of diffusion tractography
Harvard University1
Magna Græcia University2
Massachusetts General Hospital/Harvard Medical School3
University of Pittsburgh4
Utrecht University5
University Medical Centre Utrecht6
Swiss Federal Institute of Technology Lausanne7
University of Verona8
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark9
Department of Applied Mathematics and Computer Science, Technical University of Denmark10
Wellesley College11
University of Lausanne12
DeepHealth, Inc.13
QMENTA, Inc.14
University of Rochester School of Medicine and Dentistry15
Vanderbilt University16
Aalto University17
University of Wisconsin-Madison18
Eindhoven University of Technology19
University of North Carolina at Chapel Hill20
University of Sussex21
Yeditepe University22
...and 12 moreWe present results from round 2 of IronTract, the first challenge to evaluate the accuracy of tractography using i) tracer injections and diffusion MRI from the same macaque brains, and ii) DSI and HCP two-shell diffusion acquisition schemes. In round 1, only two teams achieved similarly high performance between the two different injection sites that we used for training and validation.
Here we investigate the extent to which this was due to the pre- and post-processing used by those teams. We show that, when other teams use the same pre- and post-processing, their accuracy and robustness can improve as well.
| Language: | English |
|---|---|
| Year: | 2021 |
| Proceedings: | 2021 ISMRM & SMRT Annual Meeting & Exhibition |
| Types: | Conference paper |
| ORCIDs: | Pizzolato, Marco |
