International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volume 6 Issue 6
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Deep Learning-Based Detection of Pituitary, Glioma, and Meningioma Tumors from Brain MRIs

Author(s) Brinda Roy Gupta
Country India
Abstract Brain tumors, specifically pituitary adenomas, gliomas, and meningiomas, pose a significant public health challenge, necessitating accurate and timely detection to facilitate effective treatment planning. Magnetic Resonance Imaging (MRI) is a widely adopted non-invasive imaging technique for diagnosing brain tumors. This research presents a novel methodology for detecting these tumors using MRI brain scan images. A comprehensive dataset comprising MRI scans obtained from patients diagnosed with various types of brain tumors, including pituitary adenomas, gliomas, and meningiomas, was utilized. A Convolutional Neural Network (CNN) was employed to discern between different types of brain tumors. The CNN-based model outperformed other classification algorithms, achieving an overall accuracy of 97%. This research significantly contributes to the advancement of a dependable and efficient approach for the early detection and classification of pituitary adenomas, gliomas, and meningiomas using MRI brain scan images, with potential implications for improved clinical decision-making, facilitating timely intervention, and ultimately enhancing patient outcomes in the field of neuro-oncology.
Keywords Brain tumors, Convolutional Neural Networks, deep learning, Magnetic Resonance Imaging, neuro-oncology
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 4, July-August 2024
Published On 2024-07-27
Cite This Deep Learning-Based Detection of Pituitary, Glioma, and Meningioma Tumors from Brain MRIs - Brinda Roy Gupta - IJFMR Volume 6, Issue 4, July-August 2024. DOI 10.36948/ijfmr.2024.v06i04.25294
DOI https://doi.org/10.36948/ijfmr.2024.v06i04.25294
Short DOI https://doi.org/gt5hhv
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E-ISSN 2582-2160
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