Literature DB >> 29332955

Simultaneous segmentation and bias field estimation using local fitted images.

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


  17 in total

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6.  A Variational Approach to Simultaneous Image Segmentation and Bias Correction.

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Authors:  Li Wang; Feng Shi; Gang Li; Yaozong Gao; Weili Lin; John H Gilmore; Dinggang Shen
Journal:  Neuroimage       Date:  2013-08-19       Impact factor: 6.556

9.  An active contour model for the segmentation of images with intensity inhomogeneities and bias field estimation.

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Journal:  PLoS One       Date:  2015-04-02       Impact factor: 3.240

10.  Active Contours Driven by Multi-Feature Gaussian Distribution Fitting Energy with Application to Vessel Segmentation.

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Journal:  PLoS One       Date:  2015-11-16       Impact factor: 3.240

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