CT images with expert manual contours of thoracic cancer for benchmarking auto‐segmentation accuracy-Reference-Cited by-同舟云学术

CT images with expert manual contours of thoracic cancer for benchmarking auto‐segmentation accuracy

Published:2020-03-28 Issue:7 Volume:47 Page:3250-3255
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Yang Jinzhong¹,Veeraraghavan Harini²,Elmpt Wouter³,Dekker Andre³,Gooding Mark⁴,Sharp Greg⁵

Affiliation:

1. Department of Radiation Physics The University of Texas MD Anderson Cancer Center Houston TX USA

2. Department of Medical Physics Memorial Sloan Kettering Cancer Centre New York NY USA

3. Department of Radiation Oncology (MAASTRO) GROW ‐ School for Oncology and Developmental Biology Maastricht University Medical Center Maastricht The Netherlands

4. Mirada Medical Ltd Oxford UK

5. Department of Radiation Oncology Massachusetts General Hospital Boston MA USA

Funder

National Cancer Institute

National Institutes of Health

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14107

Reference25 articles.

1. Guidance document on delivery, treatment planning, and clinical implementation of IMRT: Report of the IMRT subcommittee of the AAPM radiation therapy committee

2. Evaluation of Automatic Atlas-Based Lymph Node Segmentation for Head-and-Neck Cancer

3. A statistical modeling approach for evaluating auto-segmentation methods for image-guided radiotherapy

4. Clinical Validation of Atlas-Based Auto-Segmentation of Multiple Target Volumes and Normal Tissue (Swallowing/Mastication) Structures in the Head and Neck

5. Retrospective validation and clinical implementation of automated contouring of organs at risk in the head and neck: a step toward automated radiation treatment planning for low‐ and middle‐income countries;McCarroll R;J Global Oncol,2018

Cited by 15 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. Segmentation of Planning Target Volume in CT Series for Total Marrow Irradiation Using U-Net;2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS);2023-06

2. Automatic Multiple Articulator Segmentation in Dynamic Speech MRI Using a Protocol Adaptive Stacked Transfer Learning U-NET Model;Bioengineering;2023-05-22

3. Automated Contouring and Planning in Radiation Therapy: What Is ‘Clinically Acceptable’?;Diagnostics;2023-02-10

4. A novel multi-scale CNNs for false positive reduction in pulmonary nodule detection;Expert Systems with Applications;2022-11

5. Quality Assurance for AI-Based Applications in Radiation Therapy;Seminars in Radiation Oncology;2022-10