Computer-aided diagnosis in mammography: classification of mass and normal tissue by texture analysis

Computer-aided diagnosis in mammography: classification of mass and normal tissue by texture analysis.

Computer-aided diagnosis schemes are being developed to assist radiologists in mammographic interpretation. In this study, we investigated whether texture features could be used to distinguish between mass and non-mass regions in clinical mammograms. Forty-five regions of interest (ROIs) containing true masses with various degrees of visibility and 135 ROIs containing normal breast parenchyma w...

Computer Aided Diagnosis In Digital Mammography: Classification Of Mass And Normal Tissue by

Computer-aided classification of mammographic masses and normal tissue: linear discriminant analysis in texture feature space.

We studied the effectiveness of using texture features derived from spatial grey level dependence (SGLD) matrices for classification of masses and normal breast tissue on mammograms. One hundred and sixty-eight regions of interest (ROIS) containing biopsy-proven masses and 504 ROIS containing normal breast tissue were extracted from digitized mammograms for this study. Eight features were calcu...

Computer-Aided Detection and Diagnosis in Mammography

Screening mammography is the most effective tool for early detection of breast cancer. In this procedure, radiologists scan x-ray images of the breast to locate signs of breast cancer. However it is not perfect and has low sensitivity for detection and low specificity for diagnosis. Various computer aided detection (CAD) and diagnosis (CADx) systems have been developed to aid radiologists. In t...

Computer aided mass detection in mammography with temporal change analysis

This paper presents a method to extract change information from temporal mammogram pairs and to incorporate the temporal change information in the malignant mass classification. In this method, a temporal mammogram registration framework which is based on spatial relations between regions of interest and graph matching was used to create correspondences between regions of current mammogram and ...