Automated Contusion Volume Measurements from Acute Phase CT Predict Post-traumatic Epilepsy (S17.004)
Evaluate whether convolutional neural network (CNN)-based automated quantitative contusion measurements can predict the development of post-traumatic epilepsy (PTE).
Authors
- Brian L. Edlow (ORCID: https://orcid.org/0000-0001-7235-8456)
- Emily J. Gilmore (ORCID: https://orcid.org/0000-0002-4659-6861)
- K Chow
- Michael Brandon Westover (ORCID: https://orcid.org/0000-0003-4803-312X)
- Aaron F. Struck (ORCID: https://orcid.org/0000-0002-9103-1798)
- Sacit Bulent Omay (ORCID: https://orcid.org/0000-0002-3606-9267)
- Adithya Sivaraju
- Daniel Jin (ORCID: https://orcid.org/0000-0002-9187-1279)
- Sahar F. Zafar (ORCID: https://orcid.org/0000-0001-5252-5376)
- Samuel B. Snider (ORCID: https://orcid.org/0000-0002-6965-7890)
- Lawrence J. Hirsch (ORCID: https://orcid.org/0000-0002-6333-832X)
- Taylor Frantz (ORCID: https://orcid.org/0000-0002-9450-0529)
- Justin Wheelock (ORCID: https://orcid.org/0009-0007-9339-0798)
- Jennifer Kim (ORCID: https://orcid.org/0000-0002-3564-9892)
- J. Appleton
- M. Arsalan Bashir
- B. Berke Ayvaz
Institutions
- Hadassah Medical Center (IL)
- UW Health University Hospital (US)
- Yale University (US)
- Massachusetts General Hospital (US)
Publication Details
- Journal
- Neurology
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1212/wnl.0000000000210935
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00