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@article{176823,
        author = {KARTHIKEYAN S},
        title = {ULTRASOUND NERVE SEGMENTATION USING DEEP LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {6245-6247},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176823},
        abstract = {The Ultrasound Nerve Segmentation Using Deep Learning project leverages Convolutional Neural Networks (CNN) to detect brain tumors from ultrasound images. The system enhances diagnostic accuracy and speed by converting uploaded images to grayscale, performing image segmentation, and classifying them using a trained neural network. The model is built on a dataset from Kaggle containing both tumor and healthy images. This deep learning approach aims to improve the reliability and efficiency of brain tumor detection in medical imaging.},
        keywords = {Deep Learning, CNN, Ultrasound Imaging, Nerve Segmentation, Brain Tumor    Detection, Medical Image Processing, Image Segmentation.},
        month = {April},
        }