A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations-Reference-Cited by-同舟云学术

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations

Published:2017-11-16 Issue:1 Volume:13 Page:165-174
ISSN:1861-6410
Container-title:International Journal of Computer Assisted Radiology and Surgery
language:en
Short-container-title:Int J CARS

Author:

Spanier A. B.^ORCID,Caplan N.,Sosna J.,Acar B.,Joskowicz L.

Funder

Israel Ministry of Science

TUBITAK ARDEB

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Radiology Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering

Link

http://link.springer.com/article/10.1007/s11548-017-1687-1/fulltext.html

Reference34 articles.

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4. Assy N, Nasser G, Djibre A, Beniashvili Z, Elias S, Zidan J (2009) Characteristics of common solid liver lesions and recommendations for diagnostic workup. World J Gastroenterol 15:3217–27

5. Oliver JH, Baron RL (1996) Helical biphasic contrast-enhanced CT of the liver: technique, indications, interpretation, and pitfalls. Radiology 201:1–14

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