Enhancing automatic classification of hepatocellular carcinoma images through image masking, tissue changes and trabecular features

Background: Recent breakthroughs in computer vision and digital microscopy have prompted the application of such technologies in cancer diagnosis, especially in histopathological image analysis. Earlier, an attempt to classify hepatocellular carcinoma images based on nuclear and structural features...

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Bibliographic Details
Main Authors:	Maulana Abdul Aziz, Hiroshi Kanazawa, Yuri Murakami, Fumikazu Kimura, Masahiro Yamaguchi, Tomoharu Kiyuna, Yoshiko Yamashita, Akira Saito, Masahiro Ishikawa, Naoki Kobayashi, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto
Format:	Article
Language:	English
Published:	Elsevier 2015-01-01
Series:	Journal of Pathology Informatics
Subjects:	Hepatocellular carcinoma, histopathological image classification, image masking, liver tissue, liver trabecular, support vector machine
Online Access:	http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2015;volume=6;issue=1;spage=26;epage=26;aulast=Aziz

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http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2015;volume=6;issue=1;spage=26;epage=26;aulast=Aziz

Enhancing automatic classification of hepatocellular carcinoma images through image masking, tissue changes and trabecular features

Internet

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