文章基本信息

标题：A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images
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作者：Behnam Karimi ; Adam Krzyżak
期刊名称：Journal of Artificial Intelligence and Soft Computing Research
电子版ISSN：2083-2567
出版年度：2013
卷号：3
期号：4
页码：265-276
DOI：10.2478/jaiscr-2014-0019
出版社：Walter de Gruyter GmbH
摘要：In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based methods is obtained. A new segmentation method based on automatic selection of seed points and region growing is proposed and classification of lesions into two malignant and benign classes using combination of AdaBoost, Artificial Neural Network and Fuzzy Support Vector Machine classifiers and majority voting is implemented.