Abstract
Accuracy in feature extraction is an important factor in image classification and retrieval. In this paper, a breast tissue density classification and image retrieval model is introduced for breast cancer detection based on thermographic images. The new method of thermographic image analysis for automated detection of high tumor risk areas, based on two-directional two-dimensional principal component analysis technique for feature extraction, and a support vector machine for thermographic image retrievalwas tested on 400 images. The sensitivity and specificity of the model are 100% and 98%, respectively.
Highlights
CBreast density has been shown to be related to the risk of developing breast cancer since women with dense breast tissue can hide lesions, causing cancer to be detected at later stages (Wolfe, 1976)
The new method of thermographic image analysis for automated detection of high tumor risk areas, based on two-directional two-dimensional principal component analysis technique for feature extraction, and a support vector machine for thermographic image retrievalwas tested on 400 images
A novel model for classification of breast tissue and the breast image retrieval is proposed, in which the principal component analysis (PCA) and the two-dimensional principal component analysis (2D PCA) and the two-directional two-dimensional principal component analysis ((2D)2PCA) hve been used for feature extraction and dimension reduction of the thermographic images
Summary
CBreast density has been shown to be related to the risk of developing breast cancer since women with dense breast tissue can hide lesions, causing cancer to be detected at later stages (Wolfe, 1976). A breast tissue density classification and image retrieval model is introduced for breast cancer detection based on thermographic images. The new method of thermographic image analysis for automated detection of high tumor risk areas, based on two-directional two-dimensional principal component analysis technique for feature extraction, and a support vector machine for thermographic image retrievalwas tested on 400 images.
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