Segmentation of Medical Images with Intensity Inhomogeneity using Multiphase Level Set Functions

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    In this paper, concurrent segmentation and bias removal is proposed on magnetic resonance images with intensity inhomogeneity. Intensity inhomogeneity is basically a smoothest variation, which makes a homogeneous region of intensity an inhomogeneous. Inhomogeneity leads to poor performance of image processing algorithms in particular, in medical image processing algorithms. In this paper a level set function based solution is proposed with a variety of control over the inhomogeneity. The intensity of an individual region is modelled using Gaussian distribution with mean and variance that spatially vary. The distribution overlap between different regions is suppressed significantly using a new intensity domain. An ML function is defined for every point on the newly defined domain and a level set is formulated. The proposed method is found to be initialization robust hence can be used readily for applications and also has an extra facility in terms of iterations to exploit thinner sharper boundaries.

     

     


     

  • Keywords


    bias correction; image segmentation; intensity inhomogeneity; level set function.

  • References


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Article ID: 22971
 
DOI: 10.14419/ijet.v7i3.20.22971




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