Hybrid PSO Neuro-fuzzy System For Ultra Sound Image Segmentation

Micro-calcifications are difficult to be detected as they are variable in shape and size and may be embedded in areas of solid parenchymal tissues. The difficult tasks of medical diagnosis, in general, are the subjectivity of the pattern recognition by diagnosis experts. This is the fact in which the results are depended on the elucidation of the input from the patients but not on organized procedures. In this paper, an adaptive neuro-fuzzy model optimized by PSO algorithms has been proposed. The symptoms are gathered and the fuzzy membership values are defined. Feed forward multilayer networks are used to accept the fuzzy input values and is trained using back- propagation algorithm. The system is tested for detecting the micro-calcifications in breast sonograms. Later the results are compared for its performance.