Texture-specific bag of visual words model and spatial cone matching-based method for the retrieval of focal liver lesions using multiphase contrast-enhanced CT images-Reference-Cited by-同舟云学术

Texture-specific bag of visual words model and spatial cone matching-based method for the retrieval of focal liver lesions using multiphase contrast-enhanced CT images

Published:2017-11-05 Issue:1 Volume:13 Page:151-164
ISSN:1861-6410
Container-title:International Journal of Computer Assisted Radiology and Surgery
language:en
Short-container-title:Int J CARS

Author:

Xu Yingying,Lin Lanfen,Hu Hongjie,Wang Dan,Zhu Wenchao,Wang Jian,Han Xian-Hua,Chen Yen-Wei

Funder

National Key Basic Research Program of China

Grant-in Aid for Scientific Research from the Japanese Ministry for Education, Science, Culture and Sports (MEXT)

National Key Research and Development Program of China

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/s11548-017-1671-9/fulltext.html

Reference44 articles.

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3. Diamant I, Hoogi A, Beaulieu CF, Safdari M, Klang E, Amitai M, Rubin DL (2016) Improved patch-based automated liver lesion classification by separate analysis of the interior and boundary regions. IEEE J Biomed Health Inform 20(6):1585–1594

4. Napel SA, Beaulieu CF, Rodriguez C, Cui J, Xu J, Gupta A, Korenblum D, Greenspan H, Ma Y, Rubin DL (2010) Automated retrieval of CT images of liver lesions on the basis of image similarity: method and preliminary results 1. Radiology 256(1):243–252

5. Akgül CB, Rubin DL, Napel S, Beaulieu CF, Greenspan H, Acar B (2011) Content-based image retrieval in radiology: current status and future directions. J Digit Imaging 24(2):208–222

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