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@article{198286,
        author = {Akila V and Vasuki H and Sathvika R and Ronaldo G R},
        title = {Intelligent Brain Tumor Detection Using Deep Learning on MRI Scans},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {13440-13447},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198286},
        abstract = {Brain tumors are one of the most dangerous and important neurological disorders. Finding the disorders early and correctly identifying them are very important for getting better results. Traditionally, identifying the disorders is done by hand by looking at medical images. Magnetic Resonance Imaging (MRI) is one of the medical images used to find out what is wrong with someone. It takes a lot of time to manually analyze a medical image, and it depends a lot on the skills of the medical professionals. Automated analysis of medical images is now possible thanks to deep learning techniques.
This research proposes a brain tumor detection and classi-fication system based on the algorithm Convolutional Neural Network (CNN). In this research, the proposed system is used to identify the presence of brain tumors and the type of tumor with high precision. In this research, the dataset used is the MRI brain image with four main classes: Glioma, Meningioma, Pituitary and No tumor. To make the proposed system work better, image preprocessing techniques are used. Deep learning is used to train the CNN model, which means that the model learns to recognize the complicated patterns in MRI scan images. The model has several layers of convolution, batch normalization, activation, and residual blocks. These layers help the model learn the spatial features in the images. We judge how well the model works by how accurately it classifies the testing dataset. The experimental outcomes demonstrate that the proposed system can accurately classify various types of brain tumors, facilitating early diagnosis and treatment by medical professionals. The proposed system proves that deep learning-based approaches have immense potential in medical diagnostics, and the brain tumor detection system can be highly effective in improving the efficiency of brain tumor diagnosis.},
        keywords = {brain tumor, MRI, Convolution Neural Network (CNN).},
        month = {April},
        }