Brain tumor detection using artificial convolutional neural networks

TL;DR

This paper presents a CNN-based approach for classifying brain tumors in NMR images, achieving high accuracy and precision, demonstrating the effectiveness of deep learning in medical image diagnosis.

Contribution

The study introduces a CNN model specifically designed for brain tumor classification with high accuracy and precision, advancing automated medical image analysis.

Findings

Achieved 100% training accuracy

Attained 96% precision in evaluation

Successfully classified four tumor types

Abstract

In this paper, a convolutional neural network (CNN) was used to classify NMR images of human brains with 4 different types of tumors: meningioma, glioma and pituitary gland tumors. During the training phase of this project, an accuracy of 100% was obtained, meanwhile, in the evaluation phase the precision was 96%.