Brain Tumor Detetction Using AI: A Deep Learning Approach using a CNN model

Brain tumors pose a significant threat to human health, making early detection crucial for effective treatment. This study explores the application of deep learning techniques, particularly the VGG-16 model, for brain tumor classification. The proposed model processes MRI images to distinguish between tumor and non-tumor cases with high accuracy. The system is implemented using Python, TensorFlow, and OpenCV, with a web-based deployment for real-time predictions

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-03-31
DOI
https://doi.org/10.22214/ijraset.2025.67838
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

Brain Tumor Detetction Using AI: A Deep Learning Approach using a CNN model

Divya Mundlik
International Journal for Research in Applied Science and Engineering Technology
Brain Tumor Detection and Classification
article

Brain Tumor Detetction Using AI: A Deep Learning Approach using a CNN model

Divya Mundlik
article en

Abstract

Brain tumors pose a significant threat to human health, making early detection crucial for effective treatment. This study explores the application of deep learning techniques, particularly the VGG-16 model, for brain tumor classification. The proposed model processes MRI images to distinguish between tumor and non-tumor cases with high accuracy. The system is implemented using Python, TensorFlow, and OpenCV, with a web-based deployment for real-time predictions

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(3)
Openalex Percentile: Top 92%
Brain Tumor Detection and Classification
DOIOpen Access PDFOpenAlex
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Brain Tumor Detetction Using AI: A Deep Learning Approach using a CNN model — Divya Mundlik · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS