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Paper Details
Paper Title
A Region based Active contour Approach for Liver CT Image Analysis driven by fractional order image fitting energy
Authors
  Sajith A.G,  Dr.Hariharan S
Abstract
Computer tomography images are widely used in the diagnosis of liver tumor analysis because of its faster acquisition and compatibility with most life support devices. Accurate image segmentation is very sensitive in the field of medical image analysis.Active contours plays an important role in the area of medical image analysis.It constitute a powerful energy minimization criteria for image segmentation. This paper presents a region based active contour model for liver CT image segmentation based on variational level set formulation driven by fractional order image fitting energy. The neighbouring intensities of image pixels are described in terms of Gaussian distribution. The mean and variances of intensities in the energy functional can be estimated during the energy minimization process.The addition of the fractional order fitting term to the energy functional makes the segmentation more accurate and be robustness to noise.In order to ensure the stable evolution of the level set function a penalty term is added into the model. Also this model has been compared with different active active contour models. Our results shows that the presented model achieves superior performance in CT liver image segmentation.
Keywords- Active Contours, Fractional Order differentiation, Level sets
Publication Details
Unique Identification Number - IJEDR1702156Page Number(s) - 936-945Pubished in - Volume 5 | Issue 2 | May 2017DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Sajith A.G,  Dr.Hariharan S,   "A Region based Active contour Approach for Liver CT Image Analysis driven by fractional order image fitting energy", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 2, pp.936-945, May 2017, Available at :http://www.ijedr.org/papers/IJEDR1702156.pdf
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