An interactive deep-learning workflow for head and neck gross tumour volume segmentation

Background and purpose: Deep learning (DL)-based auto-segmentation of head and neck cancer (HNC) gross tumour volumes remains challenging due to anatomical complexity and limited accuracy. We propose an interactive DL (iDL) workflow that integrates clinician input to enhance segmentation performance...

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Bibliographic Details
Main Authors: Zixiang Wei, Jintao Ren, Jesper Grau Eriksen, Kenneth Jensen, Hanna Rahbek Mortensen, Stine Sofia Korreman, Jasper Nijkamp
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Physics and Imaging in Radiation Oncology
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Online Access:http://www.sciencedirect.com/science/article/pii/S2405631625001253
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