Detection of architectural distortion in mammograms using phase portraits

Architectural distortion is a subtle abnormality in mammograms, and a source of overlooking errors by radiologists. Computer-aided diagnosis (CAD) techniques can improve the performance of radiologists in detecting masses and calcifications; however, most CAD systems have not been designed to detect architectural distortion. We present a new method to detect and localize architectural distortion by analyzing the oriented texture in mammograms. A bank of Gabor filters is used to obtain the orientation field of the given mammogram. The orientation field is filtered and downsampled, to reduce noise and also to reduce the computational effort required by the subsequent methods. The downsampled orientation field is analyzed to produce three phase portrait maps: node, saddle, and spiral. The node map is linearly filtered, thresholded, and morphologically filtered to detect architectural distortion. The method was tested with 18 mammograms containing architectural distortion. In a preliminary experiment, a sensitivity of 88% was obtained at 15 false positives per image. Several possibilities for the improvement of the technique are being explored. A qualitative analysis of the performance of the method with stellate lesions indicates potential for enhancement of the technique.