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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREMWP0987

Predicting Meningioma Using Inception and Efficient Net Algorithms

Stream/Area:

-

Subject:

-

Paper ID:

IJSREMWP0987

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

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

CA

Chokkalla Ankith

DSCV

Dr. S China Venkateswarlu

DVSN

Dr. V Siva Nagaraju

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Abstract

Meningioma is the most common primary brain tumor, accounting for more than 30% of all brain tumors. Meningiomas originate in the meninges, the outer three layers of tissue that cover and protect the brain just under the skull. Women are diagnosed with meningiomas more often than men. About 85% of meningiomas are noncancerous, slow-growing tumors. Almost all meningiomas are considered benign, but some meningiomas can be persistent and come back after treatment. This LGG is treated with a combination of surgery and examination by monitoring the meningioma with brain MRI scans. The study of this project enabled us to build a fully automated system for segmentation of meningioma utilizing computer vision techniques, and developing models that would allow high-quality LGG identification in the brain MRI would potentially be automated to identify the genomic subtype of the meningioma by rapid and inexpensive imaging. The methods, techniques, advantages and their limitations and their future challenges are discussed in this project..

KEYWORDS

LGG MRI Inception Efficient Net CNN

Cite This Article

Chokkalla Ankith, Dr. S China Venkateswarlu, Dr. V Siva Nagaraju, "Predicting Meningioma Using Inception and Efficient Net Algorithms," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025.

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Publication Date

5/26/2025

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Double-Blind Peer Review

Review Rounds: 2

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5

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

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