SalientNet: mechanistic and reliable saliency maps for medical image classification via unsupervised learning
- DOI
- 10.1007/s11548-026-03812-y
- Published
- 2026-10-29
- Container
- International Journal of Computer Assisted Radiology and Surgery
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s11548-026-03812-y,
title = {SalientNet: mechanistic and reliable saliency maps for medical image classification via unsupervised learning},
author = {Siddhaarth Sekar and R. T. Akash Guna and Miguel A. González Ballester and O. K. Sikha},
year = {2026},
journal = {International Journal of Computer Assisted Radiology and Surgery},
doi = {10.1007/s11548-026-03812-y},
url = {https://doi.org/10.1007/s11548-026-03812-y}
}RIS
TY - JOUR TI - SalientNet: mechanistic and reliable saliency maps for medical image classification via unsupervised learning AU - Siddhaarth Sekar AU - R. T. Akash Guna AU - Miguel A. González Ballester AU - O. K. Sikha PY - 2026 JO - International Journal of Computer Assisted Radiology and Surgery DO - 10.1007/s11548-026-03812-y UR - https://doi.org/10.1007/s11548-026-03812-y ER -
APA
Sekar, S., Guna, R. T. A., Ballester, M. A. G., & Sikha, O. K. (2026). SalientNet: mechanistic and reliable saliency maps for medical image classification via unsupervised learning. International Journal of Computer Assisted Radiology and Surgery. https://doi.org/10.1007/s11548-026-03812-y
Source records
- crossref · retrieved 2026-11-07T15:36:59.260Z