A multidomain fusion model of radiomics and deep learning to discriminate between PDAC and AIP based on 18F-FDG PET/CT images-Reference-Cited by-同舟云学术

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A multidomain fusion model of radiomics and deep learning to discriminate between PDAC and AIP based on 18F-FDG PET/CT images

Published:2022-11-21 Issue:4 Volume:41 Page:417-427
ISSN:1867-1071
Container-title:Japanese Journal of Radiology
language:en
Short-container-title:Jpn J Radiol

Author:

Wei Wenting,Jia Guorong,Wu Zhongyi,Wang Tao,Wang Heng,Wei Kezhen,Cheng Chao,Liu Zhaobang^ORCID,Zuo Changjing

Funder

National Natural Science Foundation of China

234 Discipline Climbing Plan of the First Affiliated Hospital of Naval Medical University

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging

Link

https://link.springer.com/content/pdf/10.1007/s11604-022-01363-1.pdf

Reference45 articles.

1. Cascinu S, Falconi M, Valentini V, Jelic S, Group EGW. Pancreatic cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2010;21(suppl5):v55–8.

2. Natália Alves MS, Litjens G, Bosma JS, Hermans J, Huisman H. Fully automatic deep learning framework for pancreatic ductal adenocarcinoma detection on computed tomography. Cancers (Basel). 2021;14(2):376.

3. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2021. CA Cancer J Clin. 2021;71(1):7–33.

4. Anderson EM, Thomassian S, Gong J, Hendifar A, Osipov A. Advances in pancreatic ductal adenocarcinoma treatment. Cancers (Basel). 2021;13(21):5510.

5. Ogawa H, Takehara Y, Naganawa S. Imaging diagnosis of autoimmune pancreatitis: computed tomography and magnetic resonance imaging. J Med Ultrason. 2021;48(4):565–71.

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