Evaluating the Effectiveness of Deep Learning Contouring across Multiple Radiotherapy Centres-Reference-Cited by-同舟云学术

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Evaluating the Effectiveness of Deep Learning Contouring across Multiple Radiotherapy Centres

Published:2022-10 Issue: Volume:24 Page:121-128
ISSN:2405-6316
Container-title:Physics and Imaging in Radiation Oncology
language:en
Short-container-title:Physics and Imaging in Radiation Oncology

Author:

Walker Zoe,Bartley Gary,Hague Christina,Kelly Daniel,Navarro Clara,Rogers Jane,South Christopher,Temple Simon,Whitehurst Philip,Chuter Robert

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Radiation

Reference30 articles.

1. Prospective randomized double-blind study of atlas-based organ-at-risk auto segmentation-assisted radiation planning in head and neck cancer;Walker;Radiother Oncol,2014

2. Interobserver variation in clinical target volume and organs at risk segmentation in post-parotidectomy radiotherapy: can segmentation protocols help?;Mukesh;Br J Radiol,2012

3. Observer variation in target volume delineation of lung cancer related to radiation oncologist-computer interaction: a ’Big Brother’ evaluation;Steenbakkers;Radiother Oncol,2005

4. Variations in inter-observer contouring and its impact on dosimetric and radiobiological parameters for intensity-modulated radiotherapy planning in treatment of localised prostate cancer;Bhardwaj;J Radiother Pract,2008

5. 3D Variation in delineation of head and neck organs at risk;Brouwer;Radiat Oncol,2012

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. How Long Does Contouring Really Take? Results of the Royal College of Radiologists Contouring Surveys;Clinical Oncology;2024-06

2. Gross failure rates and failure modes for a commercial AI‐based auto‐segmentation algorithm in head and neck cancer patients;Journal of Applied Clinical Medical Physics;2024-01-23

3. Comparing multi-image and image augmentation strategies for deep learning-based prostate segmentation;Physics and Imaging in Radiation Oncology;2024-01

4. Clinical acceptability of automatically generated lymph node levels and structures of deglutition and mastication for head and neck radiation therapy;Physics and Imaging in Radiation Oncology;2024-01

5. Validation of a deep-learning segmentation model for adult and pediatric head and neck radiotherapy in different patient positions;Physics and Imaging in Radiation Oncology;2024-01

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