| Literature DB >> 29332955 |
Lei Wang1, Jianbing Zhu2,3, Mao Sheng4, Adriena Cribb1, Shaocheng Zhu1, Jiantao Pu1.
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.Entities:
Keywords: Bias field; Image segmentation; Intensity inhomogeneity; Level set; Local fitted images
Year: 2017 PMID: 29332955 PMCID: PMC5761354 DOI: 10.1016/j.patcog.2017.08.031
Source DB: PubMed Journal: Pattern Recognit ISSN: 0031-3203 Impact factor: 7.740