Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI-Reference-Cited by-同舟云学术

Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI

Published:2019-04-23 Issue:7 Volume:29 Page:3338-3347
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Hamm Charlie A.,Wang Clinton J.,Savic Lynn J.,Ferrante Marc,Schobert Isabel,Schlachter Todd,Lin MingDe,Duncan James S.,Weinreb Jeffrey C.,Chapiro Julius,Letzen Brian

Funder

RSNA Research and Education Foundation

National Cancer Institute

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s00330-019-06205-9.pdf

Reference27 articles.

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4. Mitchell DG, Bruix J, Sherman M, Sirlin CB (2015) LI-RADS (Liver Imaging Reporting and Data System): summary, discussion, and consensus of the LI-RADS Management Working Group and future directions. Hepatology 61:1056–1065

5. Yasaka K, Akai H, Abe O, Kiryu S (2018) Deep learning with convolutional neural network for differentiation of liver masses at dynamic contrast-enhanced CT: a preliminary study. Radiology 286:887–896. https://doi.org/10.1148/radiol.2017170706

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