Fully automatic and segmentation-robust classification of breast tumors based on local texture analysis
Bo Liu1, H. D. Cheng, Jianghua Huang, Jiafeng Liu, Tang XIanglong
1Harbin Institute of Technology
Available Online December 2008.
- 10.2991/jcis.2008.33How to use a DOI?
- texture classification, support vector machine (SVM), computer aided diagnosis, breast ultrasound (BUS) imaging
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.
- © 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/).
Cite this article
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 -