Brain Tumor Detection and Classification Using Artificial intelligence

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Abstract

The rapid development of artificial intelligence has brought new solutions in the field of medicine, especially in the analysis of medical images. The program introduces a new method called "Brain Tumor Detection, Classification Using Artificial Intelligence" to identify brain tumors accurately, efficiently. The system integrates the latest Technology that includes the YOLOV2 algorithm for tumor detection and the Mobile NetV2 architecture for tumor classification. This paper utilizes MATLAB environment, with graphics processing capabilities and artificial intelligence toolbox. The YOLOV2 algorithm is known for its ability to detect real objects and has been used to identify brain tumors in MRI scans. The system focuses on dividing tumors into two groups: benign and malignant. Mobile NetV2 architecture for tumor classification is recognized for its effectiveness and efficiency in clinical data processing. This model was developed using data containing MRI images of brain tumors.

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Keywords

MRI images, Machine Learning, Deep Learning, Artificial Intelligence, Malignant, Benign