Leveraging Persistent Homology for Liver Tumour Classification
Medical Imaging 2025: Computer-Aided Diagnosis, Proceedings of SPIE 13407, 134071Q.
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This conference paper is recorded in Medical Imaging 2025: Computer-Aided Diagnosis (2025). This page consolidates verified bibliographic metadata and the external records or research artifacts listed here.
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- Work type
- Conference paper
- Year
- 2025
- Publication date
- 2025-04-04
- Status
- Published
- Venue
- Medical Imaging 2025: Computer-Aided Diagnosis
- Publisher
- SPIE
- Volume
- 13407
- Pages
- 407-417
- Article
- 134071Q
- Last verified
- 2026-08-02
Research topics
- persistent homology
- topological data analysis
- liver tumor classification
- medical imaging
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Dashti A. Ali, Jacob J. Peoples, Ramtin Mojtahedi, Kaitlyn S. Kobayashi, William R. Jarnagin, Richard K. G. Do, and Amber L. Simpson. “Leveraging Persistent Homology for Liver Tumour Classification.” Medical Imaging 2025: Computer-Aided Diagnosis, Proceedings of SPIE 13407, 134071Q. https://doi.org/10.1117/12.3045640
@inproceedings{Ali2025PersistentHomology,
author = {Dashti A. Ali and Jacob J. Peoples and Ramtin Mojtahedi and Kaitlyn S. Kobayashi and William R. Jarnagin and Richard K. G. Do and Amber L. Simpson},
title = {{Leveraging Persistent Homology for Liver Tumour Classification}},
year = {2025},
booktitle = {Medical Imaging 2025: Computer-Aided Diagnosis},
volume = {13407},
pages = {407-417},
publisher = {SPIE},
doi = {10.1117/12.3045640},
url = {https://doi.org/10.1117/12.3045640}
}
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