@inproceedings{1b00d5cbfced45d39a46013dfec1c780,
title = "Multifractal feature based cancer detection for pathological images",
abstract = "This paper presents a significant multifractal feature description based texture discriminating technique to examine the cancer and non-cancer regions in pathological images. We acquired the characteristics (local singularity and global regularity information) of the texture using multifractal computation and used them to discriminate the highly complex visual patterns shown in the pathological images. The proposed feature description method was applied two different samples of pathological cancer liver images in different magnifications (given by digital slider) with different patch sizes (patch is a local window that we used to capture the data for training and testing). The outcomes of the experiments indicate that the proposed multifractal feature description based texture classification method is remarkable.",
keywords = "Component, Digital slider, Fractal dimension, Multifractal analysis, Pathological images, Texture classification",
author = "Chamidu Atupelage and Hiroshi Nagahashi and Michiie Sakamoto and Masahiro Yamaguchi and Akinori Hashiguchi",
year = "2011",
month = jul,
day = "14",
doi = "10.1109/icbbe.2011.5780208",
language = "English",
isbn = "9781424450893",
series = "5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011",
booktitle = "5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011",
note = "5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011 ; Conference date: 10-05-2011 Through 12-05-2011",
}
