Rectal cancer segmentation via HHF-SAM: a hierarchical hypercolumn-guided fusion segment anything model

This study presents an SAM-based framework optimized for the unique characteristics of abdominal CT images, effectively overcoming the limitations of general segmentation models in medical image processing. The proposed HHF-SAM provides a reliable tool for clinical auxiliary diagnosis, reducing inter-reader variability and improving efficiency in lesion delineation.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2026-01-12
DOI
https://doi.org/10.3389/frai.2025.1696984
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Rectal cancer segmentation via HHF-SAM: a hierarchical hypercolumn-guided fusion segment anything model

Zhoushan Feng, Congcong Wang, Ye Wang, Ying Yang et al.
Frontiers in Artificial Intelligence
Advanced Neural Network Applications
article

Rectal cancer segmentation via HHF-SAM: a hierarchical hypercolumn-guided fusion segment anything model

Zhoushan Feng, Congcong Wang, Ye Wang, Ying Yang, Xiaohong Wu
article en

Abstract

This study presents an SAM-based framework optimized for the unique characteristics of abdominal CT images, effectively overcoming the limitations of general segmentation models in medical image processing. The proposed HHF-SAM provides a reliable tool for clinical auxiliary diagnosis, reducing inter-reader variability and improving efficiency in lesion delineation.

Frontiers in Artificial IntelligenceVol. 8
Third Affiliated Hospital of Guangzhou Medical University (CN), First Hospital of China Medical University (CN), Shenyang The Fourth Hospital of People (CN), China Medical University (CN), Guangzhou Medical University (CN)
Good health and well-being
Openalex Percentile: Top 92%
Advanced Neural Network Applications
DOIOpen Access PDFOpenAlex
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Rectal cancer segmentation via HHF-SAM: a hierarchical hypercolumn-guided fusion segment anything model — Zhoushan Feng, Congcong Wang, et al. · Frontiers in Artificial Intelligence (2026) | TGRS Research Map | TGRS