Fully automatic and segmentation-robust classification of breast tumors based on local texture analysis

DOI

10.2991/jcis.2008.33How to use a DOI?

Keywords

texture classification, support vector machine (SVM), computer aided diagnosis, breast ultrasound (BUS) imaging

Abstract

In this paper, a novel fully automatic classification method of breast tumors using ultrasound (US) image is proposed. The proposed method can be divided into two steps: “ROI generation step” and “ROI classification step”. In the ROI generation step, the proposed method fo-cuses on finding a credible ROI instead of finding the precise location of the breast tumor. In the ROI classification step, lo-cal textures in the ROI are considered with a novel strategy. Both steps were implemented by utilizing supervised tex-ture classification approach. The experi-ments demonstrate that the proposed method is effective and useful for classi-fying breast tumors.

Copyright

© 2008, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bo Liu
AU  - H. D. Cheng
AU  - Jianghua Huang
AU  - Jiafeng Liu
AU  - Tang XIanglong
PY  - 2008/12
DA  - 2008/12
TI  - Fully automatic and segmentation-robust classification of breast tumors based on local texture analysis
BT  - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
PB  - Atlantis Press
SP  - 188
EP  - 194
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2008.33
DO  - 10.2991/jcis.2008.33
ID  - Liu2008/12
ER  -