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2005 | OriginalPaper | Chapter
Microcalcification Patterns Recognition Based Combination of Autoassociator and Classifier
Authors : Wencang Zhao, Xinbo Yu, Fengxiang Li
Published in: Computational Intelligence and Security
Publisher: Springer Berlin Heidelberg
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This paper presents a microcalcification patterns recognition method based autoassociator and classifier to detect the breast cancer. It studies the autoassociative and classification abilities of a neural network approach to classify the microcalcification patterns into Benign and Malignant using some certain image structure features. The proposed technique used the combination of two kinds of neural networks, autoassociator and classifier to analyze the microcalcification. It could obtain 88% classification rate for testing dataset and 100% classification rate for training dataset.