Accurate segmentation and contrast measurement of microcalcifications in mammograms: a phantom study.

Abstract

The authors are developing a computer-aided diagnostic method to assist radiologists in differentiating between malignant and benign clustered microcalcifications in mammograms. In earlier studies we investigated shape and contrast features of microcalcifications for classification. It was found that segmentation strongly influences classification results. For this reason a phantom study has been carried out. The CDMAM phantom, consisting of a pattern of dots with known size and object contrast is used for evaluation of contrast measurement and segmentation. Dots in the range of 0.2-0.8 mm are taken as a model for microcalcifications. In this article performances of different methods for segmentation of microcalcifications are compared. An iterative method based on a Markov random field and a signal dependent criterion give satisfying results. The segmentation performances of both methods are comparable. Also the influence of the modulation transfer function on contrast estimates is determined and effect of exposure level on segmentation is analyzed.