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@article{175922,
        author = {Harini R and Priyanka M and Mohammed Hakkim N and Dr. B. Karthikeyan},
        title = {Brain Tumor Detect Neuro Predict},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {4648-4652},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175922},
        abstract = {Brain tumor detection is a critical task in medical diagnosis, where early and accurate identification can save lives. This project introduces a deep learning-based approach using a Two-Pathway-Group Convolutional Neural Network (CNN) for efficient tumor detection and segmentation in MRI scans. The model combines local and global feature extraction, improving accuracy and reducing overfitting. Key stages include preprocessing, segmentation, feature extraction, and classification. Tested on BRATS2013 and BRATS2015 datasets, the method shows higher precision and lower error rates compared to traditional techniques. This approach offers a reliable and automated solution to support radiologists in clinical practice},
        keywords = {},
        month = {April},
        }