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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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Physics and Imaging in Radiation Oncology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405631625001253 |
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