Authors : Ramesh Malyala

Volume/Issue : Volume 10 - 2025, Issue 2 - February

Google Scholar : https://tinyurl.com/yc3ptb9h

Scribd : https://tinyurl.com/vtvtsxkv

DOI : https://doi.org/10.5281/zenodo.14928626

Abstract : Image segmentation is a crucial aspect of medical image analysis, primarily used to identify and evaluate affected tumors. It involves dividing an image into distinct regions that share similar features, allowing for the extraction of valuable information. A variety of image segmentation techniques have been developed, addressing the limitations of traditional medical segmentation methods. This paper reviews medical image segmentation techniques and the use of statistical mechanics through a novel approach known as the Lattice Boltzmann method (LBM). LBM is particularly advantageous due to its ability to significantly enhance computational speed in medical image segmentation while maintaining over 95% accuracy and specificity, outperforming conventional techniques. Given the limited research on LBM in medical physics, this paper aims to provide an overview of the progress made in this area.

Keywords : Segmentation, Computed Tomography, Magnetic Resonance Imaging, Image Processing, Image Analysis, Lattice Boltz Man Method.

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