This paper discusses the hybrid system for detecting masses in mammographic images. The proposed approach analyzes mammograms in three major steps. First, a global segmentation method is applied to find regions of interest. This step uses texture features, decision trees, and a multiresolution Markov random field model. The second stage works on the output of the previous algorithm. Here, a combination of three different local segmentation methods is used, and then, some relevant features are extracted. Some of them refer to the shape of the object; others are texture parameters. The final decision is made using a linear combination of these features
No takes yet. Share an insight, caveat, or question.
Szekely et al. (2006) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: