A novel shape feature to classify microcalcifications

The cited references claim that microcalcifications from many benign regions are all round or oval. The detection of at least one roughly shaped microcalcification in a suspicious region could be an early sign of potentially developing malignant cancer. This paper proposes a shape analysis method to aid radiologists in classifying regions of interest that are difficult to diagnosis. A region growing and a gradient vector flow methods are used to obtain an ordered set of contour points of each microcalcification. A three level wavelet transform frequency analysis provides a band pass approximation of the normalized distance signature. A novel metric derived from the normalized distance signature is proposed to quantify the roughness of a microcalcification. An experiment using a large dataset is used to evaluate the robustness of the proposed roughness metric against several published shape features.