
International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 7 Issue 4
July-August 2025
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Brain Tumor Detection Using Feature Based Classification And Deep Neural Network
Author(s) | Ms. Sri Priya E, Ms. Kaviya Priya K, Mr. Naresh Kannan S, Ms. Subashini R |
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Country | India |
Abstract | A tumor is a mass of abnormal cells that accumulate forming a tissue. These cells feed on normal cells and can destroy them, one of these tumors is brain tumor which affects the nervous cell, brain cell, and membranes that surrounds the brain. Worldwide it has an impact of affecting 3.5 per 100,000 individuals. A tumor is diagnosed via imaging, brain tumor is imaged with MRI. Detection of brain tumors is more important because it gives patients a better chance at successful treatment and recovery. Checking MRI scans manually takes time and can sometimes lead to mistakes. In this project, computer-based system was used for detecting brain tumors using deep learning algorithm called Convolutional Neural Network (CNN). Dataset from Kaggle was collected which contained around 3,264 MRI images. The main objective of this work is to present a comprehensive study using CNN architecture. The CNN was used for extracting data for training, targeting problems, for validation method and for quantitative performance. Primarily it looks for patterns in the image using special filters then finally undergoes Decision making network that figures out whether the tumor is present. CNN algorithm shows the complete pass of entire training dataset through epoch. Confusion matrix was done which shows the performance of the trained model by showing the counts of true positives, true negatives, false positive and false negative. Final model reached an accuracy of 96.47%, with high precision and recall, which means that it was both accurate and dependable in identifying tumors. This shows that deep learning, especially CNN can be a powerful tool to help doctors detect brain tumors more quickly and accurately. With more testing, this kind of system could be used in real hospitals to support radiologists and improve diagnosis. |
Keywords | Brain Tumor, Convolutional Network, Confusion matrix, Machine Learning, Data Analysis, Healthcare. |
Field | Engineering |
Published In | Volume 7, Issue 4, July-August 2025 |
Published On | 2025-07-23 |
DOI | https://doi.org/10.36948/ijfmr.2025.v07i04.51811 |
Short DOI | https://doi.org/g9t2gg |
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E-ISSN 2582-2160

CrossRef DOI is assigned to each research paper published in our journal.
IJFMR DOI prefix is
10.36948/ijfmr
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