Usefulness of Texture Analysis for Computerized Classification of Breast Lesions on Mammograms |
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Authors: | Jr" target="_blank">Roberto R PereiraJr Paulo M Azevedo Marques Marcelo O Honda Sergio K Kinoshita Roger Engelmann Chisako Muramatsu Kunio Doi |
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Institution: | 1.Centro de Ciências das Imagens e Física Médica, Hospital das Clinicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo, Avenida dos Bandeirantes 3900—Campus Universitário, 14048900 Ribeirão Preto, SP Brazil ;2.Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, University of Chicago, 5841, S. Maryland Avenue, Chicago, IL 60637 USA |
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Abstract: | This work presents the usefulness of texture features in the classification of breast lesions in 5,518 images of regions of interest, which were obtained from the Digital Database for Screening Mammography that included microcalcifications, masses, and normal cases. Sixteen texture features were used, i.e., 13 were based on the spatial gray-level dependence matrix and 3 on the wavelet transform. The nonparametric K-NN classifier was used in the classification stage. The results obtained from receiver operating characteristic analysis indicated that the texture features can be used for separating normal regions and lesions with masses and microcalcifications, yielding the area under the curve (AUC) values of 0.957 and 0.859, respectively. However, the texture features were not very effective for distinguishing between malignant and benign lesions because the AUC was 0.617 for masses and 0.607 for microcalcifications. The study showed that the texture features can be used for the detection of suspicious regions in mammograms. |
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Keywords: | Mammography computer-aided diagnosis texture analysis |
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