JOURNAL ARTICLE

A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images

Behnam KarimiAdam Krzyżak

Year: 2013 Journal:   Journal of Artificial Intelligence and Soft Computing Research Vol: 3 (4)Pages: 265-276   Publisher: Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology

Abstract

Abstract 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.

Keywords:
Artificial intelligence Pattern recognition (psychology) Computer science AdaBoost Support vector machine Breast ultrasound Segmentation Feature selection Artificial neural network Feature (linguistics) Fuzzy logic Feature vector Breast cancer Mammography Cancer Medicine

Metrics

19
Cited By
5.19
FWCI (Field Weighted Citation Impact)
43
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

AI in cancer detection
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Spectroscopy and Chemometric Analyses
Physical Sciences →  Chemistry →  Analytical Chemistry

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