An Evaluation of Algorithms Applied to the Lattice Boltzmann Methods Technique for Segmentation of Medical Images

A Review




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This paper provides an overview of medical image separation techniques and statistical mechanics that rely primarily on the unconditional technique known as the lattice Boltzmann method LBM. The beauty of LBM is located in the increased computing frequency according to the medical image separation method with accuracy and specificity of more than ninety-five % compared to traditional strategies. Since clinical physics does not contain many facts about LBM, it is designed to provide an overview of the development of LBM studies. Since there is no overview paper on the progress of the studies in the LB approach, this paper provides an assessment to introduce some concepts related to the unique separation of medical images and the new LB method to investigate the hobby of fate and explore the fragmentation of clinical images. This work presents a brief evaluation of the scientific image separation techniques based mainly on the threshold, based on total neighbourhood, assembly, fragment detection, model-based, and radical technique approach Lattice Boltzmann LBM. This study had mentioned some separation techniques applied to scientific images, and emphasize that none of these problem areas have been fixed to acceptance, and significant improvements must be made to all decorated algorithms. Since LBM has speed and adaptability benefits to modelling to ensure incredible exceptional image processing with a reasonable amount of computer assets, expect this approach to become a hotspot for new studies in image processing.


Segmentation, Medical Physics, Radiation Therapy, Computed Tomography, Magnetic Resonance Imaging, Radiotherapy Planning Systems, Lattice Boltzmann Methods


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An Evaluation of Algorithms Applied to the Lattice Boltzmann Methods Technique for Segmentation of Medical Images: A Review



How to Cite

Alahmar, H. T. M. (2023). An Evaluation of Algorithms Applied to the Lattice Boltzmann Methods Technique for Segmentation of Medical Images: A Review. Journal of Engineering, Science and Technological Trends, 1(1), 22–32.