Spiculated lesion detection in digital mammogram based on artificial neural network ensemble

Authors:
Ning Li;Huajie Zhou;Jinjiang Ling;Zhihua Zhou
Affiliations:
National Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangshu, China;National Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangshu, China;National Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangshu, China;National Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangshu, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Year:
2005

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Abstract

Among breast abnormalities, spiculated lesions are one of the most difficult type of tumor to detect. In this paper, we apply a feature extraction method to generate four feature images for a single mammogram, and then partition every feature image into a series of small square blocks. The four average feature values of each block are considered as an instance describing the block. Finally we use an artificial neural network ensemble method to detect the spiculated lesions. Experiments show that the accuracy of this method is well on digital mammograms.