MT-SCnet: multi-scale token divided and spatial-channel fusion transformer network for microscopic hyperspectral image segmentation

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

Authors

Institutions

Publication Details

Journal
Frontiers in Oncology
Published
2024-12-03
DOI
https://doi.org/10.3389/fonc.2024.1469293
Citations
3
Primary Topic
Image Processing Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.96
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MT-SCnet: multi-scale token divided and spatial-channel fusion transformer network for microscopic hyperspectral image segmentation

Hongmin Gao, Xueying Cao, Haoyan Zhang, Peipei Xu et al.
3 citations
Frontiers in Oncology
Image Processing Techniques and Applications
0.96
article

MT-SCnet: multi-scale token divided and spatial-channel fusion transformer network for microscopic hyperspectral image segmentation

Hongmin Gao, Xueying Cao, Haoyan Zhang, Peipei Xu, Shuyu Fei, Zhijian Wang
article en
3 citations

Abstract

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

Frontiers in OncologyVol. 14
Nanjing University of Chinese Medicine (CN), Hohai University (CN), Nanjing Drum Tower Hospital (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 20%
Image Processing Techniques and Applications
0.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.