Towards interactive deep-learning for tumour segmentation in head and neck cancer radiotherapy

Towards interactive deep-learning for tumour segmentation in head and neck cancer radiotherapy

Background and purpose: With deep-learning, gross tumour volume (GTV) auto-segmentation has substantially been improved, but still substantial manual corrections are needed. With interactive deep-learning (iDL), manual corrections can be used to update a deep-learning tool while delineating, minimis...

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Bibliographic Details
Main Authors: Zixiang Wei, Jintao Ren, Stine Sofia Korreman, Jasper Nijkamp
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:Physics and Imaging in Radiation Oncology
Subjects:
Head and neck cancer
Radiotherapy
Tumour segmentation
Interactive deep-learning
Convolutional neural network
Online Access:http://www.sciencedirect.com/science/article/pii/S2405631622001063

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