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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Information and Communication Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
