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

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

Ram Kumar, Sweta Rani, Abahan Sarkar, Fazal Ahmed Talukdar
Copyright: © 2016 |Pages: 25
ISBN13: 9781522501404|ISBN10: 1522501401|EISBN13: 9781522501411
DOI: 10.4018/978-1-5225-0140-4.ch005
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MLA

Kumar, Ram, et al. "GPU-Based Level Set Method for MRI Brain Tumor Segmentation using Modified Probabilistic Clustering." Classification and Clustering in Biomedical Signal Processing, edited by Nilanjan Dey and Amira Ashour, IGI Global, 2016, pp. 106-130. https://doi.org/10.4018/978-1-5225-0140-4.ch005

APA

Kumar, R., Rani, S., Sarkar, A., & Talukdar, F. A. (2016). GPU-Based Level Set Method for MRI Brain Tumor Segmentation using Modified Probabilistic Clustering. In N. Dey & A. Ashour (Eds.), Classification and Clustering in Biomedical Signal Processing (pp. 106-130). IGI Global. https://doi.org/10.4018/978-1-5225-0140-4.ch005

Chicago

Kumar, Ram, et al. "GPU-Based Level Set Method for MRI Brain Tumor Segmentation using Modified Probabilistic Clustering." In Classification and Clustering in Biomedical Signal Processing, edited by Nilanjan Dey and Amira Ashour, 106-130. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-5225-0140-4.ch005

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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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