Deep Learning based Multimodal Brain MRI Tumor Classification as a Diagnostic Tool to Benefit Clinical Applications
Abstract
Brain cancer is one of the most fatal types of disease, which is caused by an abnormally growing mass of defective brain tissue. Generally, brain cancer can be divided into benign and malignant, however, based on the World Health Organization, it can also be divided into grade I, II, III, and IV tumors. Magnetic Resonance Imaging (MRI) has become a crucial tool in the diagnosis and treatment of brain tumors. However, accurately classifying brain tumor images from MRI scans remains a challenging task due to the complexity and heterogeneity of tumor characteristics. This paper presents a deep learning based classification method for brain tumor classification .The model uses DenseNet101 and EfiiicentNetB3 and achieved 90 percent accuracy using dataset from the kaggle..
Keywords:
Glioma, Brain Tumors, Classification, EfficientNet, MRI
Published
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas
This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Joel Judish, Samrudh Salas, Farhaan Zuhair, Muhammed Zakkariya M, Juby Mathew, SkinGuard: An EfficientNet Model for Skin Cancer and M-pox Detection , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Alan K George, Arpita Mary Mathew, Asin Mary Jacob, Elizabeth Antony, Shiney Thomas, Classification of Lung Cancer Subtypes Using Deep Learning Model , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Devika R Nilackal, Resmara S, Greeshma R, Griesh R, Joice P Abraham, Najma Najeeb, Shehanas K Salim, CARDAMOM PLANT DISEASE DETECTION USING ROBOT , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Rhea Maria James, Richy Sara George, Sayooj Kumar M, Nihal Muhammed Ayoob, Shan Krishna, Tintu Alphonsa Thomas, A Machine Learning Framework for Tumour Classification Using Transcriptomic and Multi-Omics Datasets , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Evelyn Susan Jacob, Joel John, Raynell Rajeev, Steve Alex , Syam Gopi , Malware Classification using Image Analysis , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Selin Sam, Ameen Shouketh, Eby Jo, Jithin Russel, Joyal Anto, Muhammed Nihal K, Animal Detection Using Footprint , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Vinayak Prakash, Tresa Mariya Denny, Vivek Subash Nair, Sonal Varghese, Tom Kurian, FEATURE EXTRACTION AND CLASSIFICATION OF CERTIFICATES USING OCR , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Thomas Mathew Jose, Mathew Abraham, Sebastian Biju , Samuel Michael , Minu Cherian , Canine Dermal Analyser: Harnessing Artificial Intelligence and Deep Learning to Revolutionize Canine Skin Disease Detection , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Alan Joseph, A K Abhinay, Dr. Gee Varghese Titus, Anagha Tess B, Adham Saheer, Fabeela Ali Rawther, Comparative Analysis of Text Classification Models for Offensive Language Detection on Social Media Platforms , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Hitha P S, Ezra Tom George, Fathima N , Izabel Joseph, Karun Jidhish, Kausalya Sumesh, A Review Based on Satellite-Based Land Cover Classification System , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
You may also start an advanced similarity search for this article.