Abstract
Although segmentation of image is very important in disease diagnosis, there still exist some difficult problems to precise segmentation, such as noise and intensity inhomogeneity. Aiming at these issues, a novel level set algorithm based on salient fitting energy is presented. We firstly transform original image into a new modality which utilises greyscale change characteristics of a local area. Secondly, a data term of salient fitting energy can be constructed by solving the deviation between new modality and input images in a neighbourhood. In addition, distance regularised term is introduced in the proposed method to remove the re-initialisation process. The experiment on a lot of medical and synthetic images demonstrate that the proposed method has good segmentation ability on the part of visual perception.
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