GPU-Based Level Set Method for MRI Brain Tumor Segmentation Using Modified Probabilistic Clustering

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Author(s): Ram Kumar (National Institute of Technology Silchar, India), Sweta Rani (Nobel Medical College and Teaching Hospital, Nepal), Abahan Sarkar (National Institute of Technology Silchar, India)and Fazal Ahmed Talukdar (National Institute of Technology Silchar, India)
Copyright: 2017
Pages: 26
Source title: Medical Imaging: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-0571-6.ch043

Keywords: Medical Information Science Reference / Medical Technologies / Medicine & Healthcare

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Abstract

The level set method (LSM) has been widely used in image segmentation due to its intrinsic nature which allows handling complex shapes and topological changes easily. We propose a new level set algorithm, which is based on probabilistic c mean objective function which incorporates intensity inhomogeneity in image and robust to noise. The computational complexity of the proposed LSM is greatly reduced by using highly parallelizable lattice Boltzmann method (LBM). So the proposed algorithm is effective and highly parallelizable. The proposed LSM is implemented using Experimental results demonstrate the performance of the proposed method.

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GPU-Based Level Set Method for MRI Brain Tumor Segmentation Using Modified Probabilistic Clustering

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