TELKOMNIKA Telecommunication Computing Electronics and Control
Adaptive segmentation algorithm based on level set model in medical imaging

TELKOMNIKA Telecommunication Computing Electronics and Control
Adaptive segmentation algorithm based on level set model in medical imaging

Active contour
Anisotropic diffusion
Euler’s equation
Medical image segmentation
Variational level set

For image segmentation, level set models are frequently employed. It offer
best solution to overcome the main limitations of deformable parametric
models. However, the challenge when applying those models in medical
images stills deal with removing blurs in image edges which directly affects
the edge indicator function, leads to not adaptively segmenting images and
causes a wrong analysis of pathologies wich prevents to conclude a correct
diagnosis. To overcome such issues, an effective process is suggested by
simultaneously modelling and solving systems’ two-dimensional partial
differential equations (PDE). The first PDE equation allows restoration using
Euler’s equation similar to an anisotropic smoothing based on a regularized
Perona and Malik filter that eliminates noise while preserving edge
information in accordance with detected contours in the second equation that
segments the image based on the first equation solutions. This approach
allows developing a new algorithm which overcome the studied model
drawbacks. Results of the proposed method give clear segments that can be
applied to any application. Experiments on many medical images in particular
blurry images with high information losses, demonstrate that the developed
approach produces superior segmentation results in terms of quantity and
quality compared to other models already presented in previeous works.

Boualem Mansouri, Abdelkader Khobzaoui, Mehdi Damou, Mohammed Chetioui, Abdelhakim Boudkhil

http://telkomnika.uad.ac.id

Feb 16, 2023

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