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  2. Volume 7, Issue 4
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Online ISSN: 2515-8260

Volume7, Issue4

Detection of tumor in brain depended on k-means clustering using GUI

    Vishal Goyal Vinay Kumar Deolia

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 560-569

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Abstract

The main purpose of this project is to identify the brain tumor utilizing graphical user interface in MATLAB software. Neoplasm is a nun manageable growth of clump in brain tissues. The identification of tumefaction can be done by using either CT (computerized tomography) scan or MRI (magnetic resonance imaging). Mostly the MRI images are preferred over CT scan as they describe functional information of the tumefaction. The approach to design this paper involves four stages: - Pre-processing, edge detection, fuzzy-means clustering, followed by segmentation. This integrated approach allows the segmentation of swelling tissues with accuracy and reproducibility compared to manual segmentation. Finally, the tumefaction affected region is clearly displayed using segmentation.
Keywords:
    brain tumor neoplasm Fuzzy c- means and Threshold segmentation
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(2020). Detection of tumor in brain depended on k-means clustering using GUI. European Journal of Molecular & Clinical Medicine, 7(4), 560-569.
Vishal Goyal; Vinay Kumar Deolia. "Detection of tumor in brain depended on k-means clustering using GUI". European Journal of Molecular & Clinical Medicine, 7, 4, 2020, 560-569.
(2020). 'Detection of tumor in brain depended on k-means clustering using GUI', European Journal of Molecular & Clinical Medicine, 7(4), pp. 560-569.
Detection of tumor in brain depended on k-means clustering using GUI. European Journal of Molecular & Clinical Medicine, 2020; 7(4): 560-569.
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