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Brain Tumor Detection System Based on Convolutional Neural Network

Year: 2025

Type: article

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.

Source: Intelmatics

DOI: 10.25105/v5i1.22135

Authors: Nanang Dwi Febrianto, Is Mardianto, Abdul Rochman, Muhammad Najih

Institution: Universitas Trisakti

Language: English

Topic: Brain Tumor Detection and Classification

Subfield: Neurology

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4407956453

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