Brain Tumor Detection System Based on Convolutional Neural Network

Early detection of brain tumours is essential to improve the effectiveness of treatment. This study develops a Convolutional Neural Network (CNN) model to detect brain tumours from MRI images. Using a dataset of 4410 images, the model was trained and tested with several CNN architectures, such as EfficientNetB0, InceptionNetV3, ResNet, MobileNet, VGG16, Model 1. Results showed that the best model achieved 97.8% accuracy, thus being able to predict brain tumours with a high degree of reliability. These findings support the application of CNNs in medical detection systems to assist doctors in faster and more accurate diagnosis.

Authors

Institutions

Publication Details

Journal
Intelmatics
Published
2025-02-26
DOI
https://doi.org/10.25105/v5i1.22135
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Brain Tumor Detection System Based on Convolutional Neural Network

Abdul Rochman, Muhammad Najih, Is Mardianto, Nanang Febrianto
Intelmatics
Brain Tumor Detection and Classification
article

Brain Tumor Detection System Based on Convolutional Neural Network

Abdul Rochman, Muhammad Najih, Is Mardianto, Nanang Febrianto
article en

Abstract

Early detection of brain tumours is essential to improve the effectiveness of treatment. This study develops a Convolutional Neural Network (CNN) model to detect brain tumours from MRI images. Using a dataset of 4410 images, the model was trained and tested with several CNN architectures, such as EfficientNetB0, InceptionNetV3, ResNet, MobileNet, VGG16, Model 1. Results showed that the best model achieved 97.8% accuracy, thus being able to predict brain tumours with a high degree of reliability. These findings support the application of CNNs in medical detection systems to assist doctors in faster and more accurate diagnosis.

IntelmaticsVol. 5(1)
Universitas Trisakti (ID)
Openalex Percentile: Top 95%
Brain Tumor Detection and Classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.