A Level Set Approach to Image Segmentation With Intensity Inhomogeneity

IEEE Transactions on Cybernetics
Kaihua ZhangDavid Zhang

Abstract

It is often a difficult task to accurately segment images with intensity inhomogeneity, because most of representative algorithms are region-based that depend on intensity homogeneity of the interested object. In this paper, we present a novel level set method for image segmentation in the presence of intensity inhomogeneity. The inhomogeneous objects are modeled as Gaussian distributions of different means and variances in which a sliding window is used to map the original image into another domain, where the intensity distribution of each object is still Gaussian but better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying a bias field with the original signal within the window. A maximum likelihood energy functional is then defined on the whole image region, which combines the bias field, the level set function, and the piecewise constant function approximating the true image signal. The proposed level set method can be directly applied to simultaneous segmentation and bias correction for 3 and 7T magnetic resonance images. Extensive evaluation on synthetic and real-images demonstrate the superiority of the proposed method over other representative algorit...Continue Reading

References

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Citations

Dec 17, 2015·IEEE Transactions on Cybernetics·Xiangzhi BaiYi Lu
Mar 23, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Fitsum MesadiTolga Tasdizen
Aug 30, 2017·Medical & Biological Engineering & Computing·Amir FaisalKhin Wee Lai
Sep 19, 2017·IEEE Transactions on Cybernetics·Xuelong LiYongsheng Dong
Aug 31, 2017·PloS One·Xiangrui MengJianwei Zhang
Apr 20, 2019·Journal of Healthcare Engineering·Yuan GaoYaoming Zhuang
May 12, 2015·Computational Intelligence and Neuroscience·Mohammed M AbdelsameaEyad Elyan
Nov 5, 2017·Scientific Reports·Farhan AkramDomenec Puig
Jan 31, 2021·Journal of Neuroscience Methods·Asieh KhosravanianSaeed Mozaffari
Mar 25, 2021·Mathematical Biosciences and Engineering : MBE·Tianran YuanYabin Xu
Jun 8, 2021·PloS One·Weiqin ChenBin Pan
Aug 13, 2021·Medical & Biological Engineering & Computing·Lingling FangYibo Yao

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