ISSN 2394-5125
 

Research Article 


MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha.

Abstract
Brain tumor segmentation of MRI imagery is very essential in detecting and analyzing brain tumors. But it's a herculean task due to the presence of noise and intensity inhomogeneity in the MRI imagery. The main motive of this paper is to develop a useful and potent methodology for automatic brain tumor segmentation of MRI images that will aid the radiologists for better diagnosis. The proposed methodology involves two processes, first process is pre-segmentation of the MRI image using SLIC superpixel algorithm and second segmentation process is based on CNN. The proposed method is validated for both real-time datasets obtained from a radiologist and datasets from an online database. The results are shown in terms of the Dice index (DICE) and the Jaccard index (JACCARD). The evaluation of performance of the proposed methodology shows that it achieves higher average values of DICE and JACCARD, which indicates good segmentation performance and better accuracy compared to existing methods.

Key words: Brain tumor, CNN, MRI, Pre-segmentation, Region of Interest (ROI), Simple Linear Iterative Clustering (SLIC)


 
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How to Cite this Article
Pubmed Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha. MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS. JCR. 2020; 7(19): 4454-4462. doi:10.31838/jcr.07.19.523


Web Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha. MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS. http://www.jcreview.com/?mno=127667 [Access: September 16, 2020]. doi:10.31838/jcr.07.19.523


AMA (American Medical Association) Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha. MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS. JCR. 2020; 7(19): 4454-4462. doi:10.31838/jcr.07.19.523



Vancouver/ICMJE Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha. MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS. JCR. (2020), [cited September 16, 2020]; 7(19): 4454-4462. doi:10.31838/jcr.07.19.523



Harvard Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha (2020) MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS. JCR, 7 (19), 4454-4462. doi:10.31838/jcr.07.19.523



Turabian Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha. 2020. MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS. Journal of Critical Reviews, 7 (19), 4454-4462. doi:10.31838/jcr.07.19.523



Chicago Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha. "MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS." Journal of Critical Reviews 7 (2020), 4454-4462. doi:10.31838/jcr.07.19.523



MLA (The Modern Language Association) Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha. "MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS." Journal of Critical Reviews 7.19 (2020), 4454-4462. Print. doi:10.31838/jcr.07.19.523



APA (American Psychological Association) Style

Panditi Sai Pavan, Yepuganti Karuna, Saladi Saritha (2020) MRI BRAIN TUMOR SEGMENTATION WITH SLIC AND CONVOLUTIONAL NEURAL NETWORKS. Journal of Critical Reviews, 7 (19), 4454-4462. doi:10.31838/jcr.07.19.523