Automatic segmentation of organs at risk and tumors in CT images of lung cancer from partially labelled datasets with a semi-supervised conditional nnU-Net-Reference-Cited by-同舟云学术

Automatic segmentation of organs at risk and tumors in CT images of lung cancer from partially labelled datasets with a semi-supervised conditional nnU-Net

Published:2021-11 Issue: Volume:211 Page:106419
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Zhang Guobin,Yang Zhiyong,Huo Bin,Chai Shude,Jiang Shan^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference41 articles.

1. Cancer statistics, 2021;Siegel;CA,2021

2. Choice of postoperative radiation for stage IIIA pathologic N2 non-small cell lung cancer: impact of metastatic lymph node number;Wang;Radiat. Oncol.,2017

3. Postoperative radiotherapy for stage II or III non-small-cell lung cancer using the surveillance, epidemiology, and end results database;Lally;J. Clin. Oncol.,2006

4. Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer;Zhang;Medicine (Baltimore).,2020

5. Delineation of target volumes and organs at risk in adjuvant radiotherapy of early breast cancer: national guidelines and contouring atlas by the Danish Breast Cancer Cooperative Group;Nielsen;Acta Oncol. (Madr),2013

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