Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods-Reference-Cited by-同舟云学术

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Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods

Published:2020-08 Issue: Volume:76 Page:294-306
ISSN:1120-1797
Container-title:Physica Medica
language:en
Short-container-title:Physica Medica

Author:

Wang Tonghe,Lei Yang,Fu Yabo,Curran Walter J.,Liu Tian,Nye Jonathon A.,Yang Xiaofeng

Funder

National Cancer Institute of the National Institutes of Health

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Radiology Nuclear Medicine and imaging,General Medicine,Biophysics

Reference163 articles.

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2. 18F-FDG PET in the detection of extrahepatic metastases from hepatocellular carcinoma;Sugiyama;J Gastroenterol,2004

3. Delayed 18F-FDG PET for detection of paraaortic lymph node metastases in cervical cancer patients;Ma;J Nucl Med,2003

4. High-risk melanoma: accuracy of FDG PET/CT with added CT morphologic information for detection of metastases;Strobel;Radiology,2007

5. Axillary lymph node metastases: screening with [F-18]2-deoxy-2-fluoro-D-glucose (FDG) PET;Adler;Radiology,1997

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