AnatomyNet: Deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy-Reference-Cited by-同舟云学术

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AnatomyNet: Deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy

Published:2018-12-17 Issue:2 Volume:46 Page:576-589
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Zhu Wentao¹,Huang Yufang²,Zeng Liang³,Chen Xuming⁴,Liu Yong⁴,Qian Zhen⁵,Du Nan⁵,Fan Wei⁵,Xie Xiaohui¹

Affiliation:

1. Department of Computer Science University of California Irvine CAUSA

2. Lenovo Research Beijing China

3. Deepvoxel Inc Shanghai China

4. Department of Radiation Oncology Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai China

5. Tencent Medical AI Lab Palo Alto CAUSA

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.13300

Reference45 articles.

1. Global cancer statistics, 2012;Torre LA;CA,2015

2. Atlas‐based auto‐segmentation of head and neck CT images;Han X;Med Image Comput Comput Assist Interv,2008

3. Vision 20/20: Perspectives on automated image segmentation for radiotherapy

4. Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015

5. Does atlas-based autosegmentation of neck levels require subsequent manual contour editing to avoid risk of severe target underdosage? A dosimetric analysis

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