A Novel Automatic Liver Segmentation by Level Set Method Over Real-Time Sensory Computed Tomography

The issues based on gastroenterology are the most distressing diseases in a human anatomy with the largest solid organ, liver that requires serious attention in its diagnosis. The challenging task of Liver segmentation is the main motive, proposed with the exploring of level set methodology with signed pressure force combined with masking and other Morphological operations. Next, the segmented liver multi-atlases are condensed together as a complete 3D projection of Human Liver in 360° shape angulation. The huge set of abdominal slices with 0.16 mm spacing of about 250 real time images of each subject, is treated as input with this proposed method and nearly 2550 CT images are used to get segmented using this methodology. The Evaluation Metrics given as 5 Error Metrics and 4 Performance Metrics obtained with the averaging of 10 atlases to each point, of the segmented atlases, outperforms the comparative methods of the Radiologist’s inference of liver boundary detection and an additional existing Local Fuzzy thresholding methodology. The overall visual outcome, evaluation metrical values and graphical data shows the peculiar performance of proposed methodology. This outcome with the electronic evolution of computed tomography appends to the wireless sensory waves to mark the CT images for our input. The doctors will be greatly helped by our process, to serve the global cause of saving lives by diagnosing accurately the complications of liver with appropriate segments, at early stage itself.