Deep learning for hepatocellular carcinoma segmentation in MRI: A systematic review of models, performance, and challenges
DL models demonstrate robust HCC segmentation performance in MRI, but dataset limitations, lesion variability, and imaging inconsistencies hinder clinical adoption. Multi-center datasets, standardized protocols, and hybrid approaches integrating radiologist input are critical for advancement.
Authors
- Nadia Najafizade (ORCID: https://orcid.org/0000-0002-1230-1084)
- Abolfazl Koozari (ORCID: https://orcid.org/0009-0009-5149-8914)
- Mohammadreza Elhaie (ORCID: https://orcid.org/0009-0007-1186-353X)
- Maryam Arjmandi
Institutions
- Isfahan University of Medical Sciences (IR)
- Ahvaz Jundishapur University of Medical Sciences (IR)
- Iran University of Medical Sciences (IR)
Publication Details
- Journal
- Medicine
- Published
- 2025-12-19
- DOI
- https://doi.org/10.1097/md.0000000000047061
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00