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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM14796

BRAIN TUMOR SEGMENTATION USING CNN

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM14796

Volume:

6 |

6 |

Jun 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM14796

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GS

Goli Shivani

MK

Muthyala Koumudhi

NH

Nagamalla Harini

ESR

Eddu Srinivasa Rao

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Abstract

Brain tumors are the most common issue in children. Now-a-days number of patients suffering from brain tumor has been increasing.Human body consist of many number of cells.Each cell divide into different number of cells to form sub cells.These subcells are also necessary for body health.If these sub cells form without any shape,then it forms tumor cells.Tumor cells are the extra cells in our body.Tumor cells are of two types.They are high grade tumor and low grade tumor.High Grade Tumor refers to Malignant Tumor which is cancerous .Low Grade Tumor is benign tumor which is non cancerous tumor. Earlier cerebrum cancer segmentation is done by doctors.but it is time taking process and we need to depend on Human skills.hence cerebrum cancer segmentation using machine learning is introduced.but in machine learning methods we need to explicitly extract features.hence we now moved to cerebrum cancer segmentation using Convolution Neural Network is introduced.In convolution neural network accuracy is high because of Back Propagation method.Hence In this work we used Brain Tumor Detection Using Convolution Neural Network (CNN).

KEYWORDS

CNN Tumor Segmentation Deep learning.

Cite This Article

Goli Shivani, Muthyala Koumudhi, Nagamalla Harini, Eddu Srinivasa Rao, "BRAIN TUMOR SEGMENTATION USING CNN," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 6, Jun 2022. https://doi.org/10.55041/IJSREM14796

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Publication Date

6/26/2022

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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