International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, Issue 1, pp. 54-59, January 2026.
This work is licensed under a Creative Commons Attribution 4.0 International License.
D. Janani
Pothu Nikitha
Osuru Manohar
R Hemanth Kumar
Bommana Nagarjuna
Challa Hemanth Kumar
Department of CSE, Siddartha Institute of Science and Technology, Puttur, India.
Abstract: Brain tumor detection can be considered one of the great uses of technology in the healthcare sector, and it may result in a significant increase in the survival rate of patients if their effective detection is done on time. The project aims to achieve maximum detection of brain tumors in MRI images using a dual-module deep learning technique. For both deep learning modules, one pertains to the image-processing task, which aims to increase image contrast and focuses on tumor segments. After image processing, another deep learning task is used to classify images extracted from MRIs as containing a tumor or not, based on the type of tumor present. This project will be implemented on public MRI image datasets, using metrics such as Accuracy, Precision, Recall, F1 Score, and ROC AUC.
Keywords: MRI, Brain Tumour, Image Enhancement, Survival Rate.
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