Boundary aware microscopic hyperspectral pathology image segmentation network guided by information entropy weight

This advance has significant implications for the field of MHSIs segmentation. Our code is freely available at https://github.com/sharycao/BE-NET.

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Publication Details

Journal
Frontiers in Oncology
Published
2025-03-27
DOI
https://doi.org/10.3389/fonc.2025.1549544
Citations
2
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
2.72
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article

Boundary aware microscopic hyperspectral pathology image segmentation network guided by information entropy weight

Hongmin Gao, Xueying Cao, Ping Zhang, Min Zhu et al.
2 citations
Frontiers in Oncology
Radiomics and Machine Learning in Medical Imaging
2.72
article

Boundary aware microscopic hyperspectral pathology image segmentation network guided by information entropy weight

Hongmin Gao, Xueying Cao, Ping Zhang, Min Zhu, Peipei Xu, Ting Qin
article en
2 citations

Abstract

This advance has significant implications for the field of MHSIs segmentation. Our code is freely available at https://github.com/sharycao/BE-NET.

Frontiers in OncologyVol. 15
Nanjing Normal University (CN), Hohai University (CN), Shanghai University of Finance and Economics (CN), Nanjing Drum Tower Hospital (CN), Nanjing Medical University (CN)
Openalex Percentile: Top 12%
Radiomics and Machine Learning in Medical Imaging
2.72
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Boundary aware microscopic hyperspectral pathology image segmentation network guided by information entropy weight — Hongmin Gao, Xueying Cao, et al. · Frontiers in Oncology (2025) | TGRS Research Map | TGRS