Multifractal feature descriptor for grading Hepatocellular carcinoma

C. Atupelage, H. Nagahashi, M. Yamaguchi, T. Abe, A. Hashiguchi, M. Sakamoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper presents a textural feature descriptor that can be effectively utilized for grading Hepatocellular carcinoma (HCC) histopathological images. The proposed feature descriptor observes the local and spatial characteristics of the texture by utilizing multifractal computation, and it is incorporated with a bag-of-feature (BOF)-based classification model to classify a set of images. We compare the proposed feature descriptor with four well-founded feature descriptors in the experiments, and benchmark the classification performances. The benchmarked results indicated the significance of the multifractal feature descriptor.

Original languageEnglish
Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
Pages129-132
Number of pages4
Publication statusPublished - 2012 Dec 1
Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
Duration: 2012 Nov 112012 Nov 15

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Other

Other21st International Conference on Pattern Recognition, ICPR 2012
CountryJapan
CityTsukuba
Period12/11/1112/11/15

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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