3D segmentation of liver and its lesions using optimized geometric contours
Ankur Biswas, Paritosh Bhattacharya, Santi P. Maity · Procedia Computer Science · 2018
An optimised accurate segmentation of liver and hepatic lesions from Computed Tomography (CT) scans can support the study of deriving quantitative biomarkers for accurate clinical diagnosis and successful conclusion of computer-assisted diagnosis and therapy. In spite of several existence of research, fully automatic segmentation of liver and its lesions still remains a challenging task. This paper presents a method for delineation of liver and its lesions in CT volume images using energy optimised geometric active contours. The abdominal region was initially determined based on maximum intensity projection (MIP) and thresholding methods to extract the liver volume of interest (VOI). Two geometric contours using level set method were initialized and cascaded for a combined segmentation of the liver and its lesions. In the first step, a contour to segment the liver was initialized that served as VOI input for a second geometric contour. The second contour exclusively segmented lesions within the predicted liver VOIs of first step. Experiments on CT image data obtained dice coefficient of 0.900, jaccard coefficient of 0.818 and other surface distance measures demonstrate the advantages of the proposed methodology in both exactness and competence.