Revolutionizing Brain Tumor Detection: The CNN-Based Medical Imaging Breakthrough

Magazine Article

Date Published: December 13, 2023

Authors

• Kushagra Agrawal
• Nisharg Nargund

Publisher

Neural Networks

DOI

10.1287/orms.2023.04.03

Abstract

A brain tumor is a typical cluster or proliferation of cells within the brain that can lead to disturbances in regular brain function and present diverse neurological symptoms. These tumors are categorized as either malignant or benign. Malignant tumors are cancerous, whereas benign tumors, though noncancerous, can still pose risks depending on their size and location. Currently, the medical community recognizes more than 120 different types of brain tumors. Brain cancer is a severe medical condition that arises from malignant brain tumors that have the potential to spread and invade neighboring tissues through the spinal fluid. Their detrimental impact is often evident when they obstruct the normal flow of fluids within the human brain.

This article presents a convolutional neural network (CNN)-based brain tumor detection model for classifying magnetic resonance imaging (MRI) images as containing tumors (YES) or not (NO). The deep learning model includes Conv2D, MaxPooling, Dense, and Flatten layers. Image segmentation is utilized to accurately detect cancerous patterns in MRI scans. Prompt early detection of tumors is vital to significantly improve patient outcomes. The model may achieve a 100% individual accuracy rate in quickly detecting small and large tumors. The implications of this model are significant, benefiting early diagnosis and treatment of brain tumors, leading to improved patient prognosis and preventing complications.

Read it here: https://doi.org/10.1287/orms.2023.04.03/full/

Authors and Affiliations

• Kushagra Agrawal, School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India
• Nisharg Nargund, School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India