Distance Regularized Level Set Evolution for Medical Image Segmentation

Abstract

Medical image is an important tool because it can be used for surgical planning and simulation, radiotherapy planning, and tracking the progress of disease. To analyze the medical image, it must partitioned into different segment using image segmentation methods. Many methods are introduced to perform that segmentation, one of them is DRLSE. DRLSE are the development of level set method and maintained by forward and backward (FAB) diffusion derived from distance regularization term. Because of that DRLSE eliminates the need for reinitialization and avoid the undesirable side effect. This research use DRLSE for medical image segmentation. DRLSE can be used in medical image segmentation.