Abstract
The analysis of medical images requires image segmentation to
distinguish the boundaries of irregular regions such as tumors in images.
However, segmentation of medical images with intensity inhomogeneity
has always been a challenging task in image processing. In this paper,
we have proposed a new model for segmentation of medical image having
inhomogeneous intensities. In the proposed model, we have used hybrid
image data obtained from the product of given image with smooth image
and difference of smooth product image from product image. The model
uses both local and global information of the image. The proposed model
outperforms the existing models qualitatively and quantitatively i.e. in
terms of number of iterations and CPU time. For the solution of proposed
model we have used some of the numerical schemes such as Explicit and
Semi-Implicit schemes. The model is further tested for different type of
real medical images. The results showed that the proposed model also performs well in images having intensity inhomogeneity and blurred edges as
wel
Hadia Atta, Noor Badshah, Syed Inayat Ali Shah, Nasru Minallah. (2019) Mathematical Model for Segmentation of Medical Images via Hybrid Images Data, Punjab University Journal of Mathematics, Volume 51, Issue 10.
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