Title :
Improved local binary patterns for classification of masses using mammography
Author :
Liu, Jun ; Liu, Xiaoming ; Chen, Jianxun ; Tang, J.
Author_Institution :
Coll. of Comput. Sci. & Technol., Wuhan Univ. of Sci. & Technol., Wuhan, China
Abstract :
In this paper, we investigate mass classification using an improved local binary pattern operator. In the proposed classification algorithm, the improved local binary pattern operator is used to extract the features of masses and is used to determine whether the mass is benign or malignant. For classifier, support vector machine is adopted. 309 images from the DDSM database were used and the experimental results show the effectiveness of the proposed algorithm.
Keywords :
feature extraction; image classification; mammography; medical image processing; support vector machines; DDSM database; feature extraction; local binary pattern operator; mammography; mass classification; support vector machine; Breast cancer; Cancer detection; Classification algorithms; Feature extraction; Support vector machines; Training; Mass classification; local binary pattern operator; median; support vector; texture analysis;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4577-0652-3
DOI :
10.1109/ICSMC.2011.6084079
