Body region localization in whole-body low-dose CT images of PET/CT scans using virtual landmarks-Reference-Cited by-同舟云学术

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Body region localization in whole-body low-dose CT images of PET/CT scans using virtual landmarks

Published:2019-01-24 Issue:3 Volume:46 Page:1286-1299
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Bai Peirui¹²,Udupa Jayaram K.²,Tong Yubing²,Xie ShiPeng²³,Torigian Drew A.²

Affiliation:

1. College of Electronics; Communication and Physics; Shandong University of Science and Technology; Qingdao Shandong 266590 China

2. Medical Image Processing Group; Department of Radiology; University of Pennsylvania; Philadelphia PA 19104 USA

3. College of Telecommunications and Information Engineering; Nanjing University of Posts and Telecommunications; Nanjing Jiangsu 210023 China

Funder

National Institutes of Health

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Medicine

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/mp.13376/fullpdf

Reference23 articles.

1. Chest fat quantification via CT based on standardized anatomy space in adult lung transplant candidates;Tong;PLoS ONE,2017

2. Optimization of abdominal fat quantification on CT imaging through use of standardized anatomic space-a novel approach;Tong;Med Phys,2014

3. Tong YB Udupa JK Wu CY Fat segmentation on chest CT images via fuzzy models 2016

4. Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images;Udupa;Med Image Anal,2014

5. Automatic anatomy recognition in whole-body PET/CT images;Wang;Med Phys,2016

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1. Application of ultra-low-dose CT in 3D printing of distal radial fractures;European Journal of Radiology;2021-02

2. BRR‐Net: A tandem architectural CNN–RNN for automatic body region localization in CT images;Medical Physics;2020-08-20

3. A Novel Framework for Improving Pulse-Coupled Neural Networks With Fuzzy Connectedness for Medical Image Segmentation;IEEE Access;2020

4. How many models/atlases are needed as priors for capturing anatomic population variations?;Medical Image Analysis;2019-12

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