Intelligent System for Multi-Class Brain Tumor  Classification

Author(s)	Kajal Kapur, Mangesh More
Country	India
Abstract	The field of medicine is undergoing a major transformation driven by Artificial Intelligence (AI). With advancements in digital data collection, machine learning techniques, and powerful computing capabilities, AI is now being applied to areas once dominated by human expertise. Brain tumors, which involve abnormal tissue growth from uncontrolled cell proliferation, present a significant health risk due to their potential malignancy. These tumors can invade and damage healthy brain tissue, resulting in severe consequences. This project explores recent advancements in AI technologies and their applications in the biomedical sector. We address the challenges that must be overcome to advance medical AI systems and examine the economic, legal, and social implications of integrating AI into healthcare. In response to these needs, we propose a novel approach for accurate brain tumor detection and classification. Our project features an intuitive interface that supports tumor detection, classification, and severity assessment. It utilizes Convolutional Neural Networks (CNNs) for reliable tumor classification and incorporates state-of-the-art machine learning algorithms to enhance performance
Keywords	CNN, Deep Learning, ResNet-50, OpenCV, TensorFlow.
Field	Engineering
Published In	Volume 4, Issue 6, November-December 2023
Published On	2023-11-02

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Advanced International Journal for Research