Shifted window-based Transformer with multimodal representation for the systematic staging of rectal cancer

Systematic staging of rectal cancer aims to determine tumor invasion degree and lymph node metastasis (LNM) status. Artificial intelligence technologies can aid physicians in making more accurate therapeutic decisions. Current research on rectal cancer segmentation primarily relies on convolutional...

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Veröffentlicht in:	Service oriented computing and applications Jg. 19; H. 3; S. 225 - 236
Hauptverfasser:	Wang, Haoyu, Li, Peihong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.09.2025 Springer Nature B.V
Schlagworte:	Artificial intelligence Artificial neural networks Cancer Classification Clinical medicine Colorectal cancer Computer Appl. in Administrative Data Processing Computer Science Computer Systems Organization and Communication Networks Datasets Diagnosis e-Commerce/e-business Efficiency IT in Business Lymphatic system Management of Computing and Information Systems Medical diagnosis Metastasis Neural networks Original Research Paper Patients Personal information Physicians Radiomics Rectum Regression analysis Representations Segmentation Software Engineering/Programming and Operating Systems Tumors Lymph node metastasis Multimodal representation Rectal cancer Swin Transformer
ISSN:	1863-2386, 1863-2394
Online-Zugang:	Volltext
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