Segmentation of CT image using MAP-Model and Simulation Annealing
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10.5120/9904-4492 |
Md. Gauhar Arefin, Mithun Kumar P K., Abu Sayem, Md Delowar Hossain and Md Motiur Rahman. Article: Segmentation of CT image using MAP-Model and Simulation Annealing. International Journal of Computer Applications 61(2):45-48, January 2013. Full text available. BibTeX
@article{key:article,
author = {Md. Gauhar Arefin and Mithun Kumar P K. and Abu Sayem and Md Delowar Hossain and Md Motiur Rahman},
title = {Article: Segmentation of CT image using MAP-Model and Simulation Annealing},
journal = {International Journal of Computer Applications},
year = {2013},
volume = {61},
number = {2},
pages = {45-48},
month = {January},
note = {Full text available}
}
Abstract
Segmentation on Computed Tomography (CT) image of heart and brain can be optimally posed as Bayesian labeling in which the segment of a image is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The Simulated Annealing (SA) algorithm is used to minimize the energy function associated with MRF posterior distribution function. The goal of this thesis paper is to minimize the energy function using Gaussian distribution and get accurate segmentation by slowly minimize the energy and simultaneously reduce the pixels which have no impact on the image at rapid rate to get the segmentation quickly without degrade the image. The propose algorithm able to get more precise segmentation.
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