A comparative study of κ-means and graph cut 3method of liver segmentation
Shraddha Sangewar, Prema M. Daigavane · 2017
Medical Imaging is a costly process due to the involvement of different machinery which is used to obtain the images of different areas of body parts. But it is an essential process to do so as to obtain maximum information regarding the images so as to view every possible essential information present in it. It is found that the images which have more gray level are difficult to extract the boundary areas cannot be separated efficiently as compare to the other dark levels. It is because of the differences in the intensity levels. Manual segmentation of liver computerized tomography (CT) images is difficult task, so it is desired to develop a system for the analysis of liver CT images that can segment the liver without any processing from humans. CT images are generally used for detection of tumor and to determine the treatment to be given to the patient. 3D volume analysis of the liver organ helps to analyse an image in view to observe the minute details which might not be visible in 2D view. In this paper comparative analysis between k-means and graph cut segmentation technique for extraction of liver organ is done and on the basis of the result obtained different parameters related to liver are computed.