AAR‐LN‐DQ: Automatic anatomy recognition based disease quantification in thoracic lymph node zones via FDG PET/CT images without Nodal Delineation-Reference-Cited by-同舟云学术

AAR‐LN‐DQ: Automatic anatomy recognition based disease quantification in thoracic lymph node zones via FDG PET/CT images without Nodal Delineation

Published:2020-06-15 Issue:8 Volume:47 Page:3467-3484
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Xu Guoping¹²,Udupa Jayaram K.²,Tong Yubing²,Odhner Dewey²,Cao Hanqiang¹,Torigian Drew A.²³

Affiliation:

1. School of Electronic Information and Communications Huazhong University of Science and technology Wuhan Hubei 430074 China

2. Medical Image Processing Group, Department of Radiology, University of Pennsylvania 602 Goddard building, 3710 Hamilton Walk Philadelphia PA 19104 USA

3. Department of Radiology Hospital of the University of Pennsylvania Philadelphia PA 19104 USA

Funder

University of Pennsylvania

China Scholarship Council

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14240

Reference33 articles.

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4. LiuY UdupaJK OdhnerD et al.Definition and automatic anatomy recognition of lymph node zones in the pelvis on CT images. In: Medical Imaging 2016: Biomedical Applications in Molecular Structural and Functional Imaging. International Society for Optics and Photonics;2016. page 97881J.

5. XuG UdupaJK TongY et al.Thoracic lymph node station recognition on CT images based on automatic anatomy recognition with an optimal parent strategy. In: Medical Imaging 2018: Image Processing. International Society for Optics and Photonics;2018. page 105742F.

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