Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4969480 | Pattern Recognition | 2018 | 24 Pages |
Abstract
Level set methods often suffer from boundary leakage and inadequate segmentation when used to segment images with inhomogeneous intensities. To handle this issue, a novel region-based level set method was developed, in which two different local fitted images are used to construct a hybrid region intensity fitting energy functional. This novel method enables simultaneous segmentation of the regions of interest and estimation of the bias fields from inhomogeneous images. Our experiments on both synthetic images and a publicly available dataset demonstrate the feasibility and reliability of the proposed method.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Lei Wang, Zhu Jianbing, Sheng Mao, Adriena Cribb, Shaocheng Zhu, Jiantao Pu,