Soft computing based segmentation of anomalies on abdomen CT images

Medical imaging is the non-invasive visualization of internal organs of the human body. In this paper a soft computing based segmentation model is proposed to segment the anomalies from the abdomen CT images. The anomalies in the abdomen CT image can be a renal cyst, tumor or renal stone. The preprocessing is done by bilateral filter for the removal of noise so that segmentation algorithm produces better results. Fuzzy c means clustering algorithm is used for the segmentation and the preprocessing result is validated by the performance metrics and statistical parameters. The proposed method was tested with real abdomen CT images of the patients. Experiments were performed on real data sets confirm the effectiveness and usefulness of the proposed method.