Computerized Diagnostic System for Brain Tumor Detection Using Artificial Intelligence

Abstract

Brain tumors are a significant health concern worldwide, and early detection plays a crucial role in improving patient outcomes. In this paper, we propose a computerized diagnostic system for brain tumor detection using artificial intelligence (AI) techniques. The aim is to develop an automated and accurate system that can assist medical professionals in the early diagnosis of brain tumors. The proposed system utilizes advanced AI algorithms, including machine learning and image processing, to analyze medical imaging data such as MRI scans. The system extracts relevant features from the images and employs a trained model to classify them as tumor or non-tumor regions. By leveraging the power of AI, the system can detect subtle abnormalities that may be indicative of a brain tumor, even at its early stages. To evaluate the performance of the system, we conducted experiments using a large dataset of brain MRI images. The results demonstrate the effectiveness and efficiency of the proposed computerized diagnostic system. Compared to traditional diagnostic approaches, our system achieves higher accuracy in detecting brain tumors, thereby aiding in timely intervention and treatment planning. The development of this computerized diagnostic system represents a significant advancement in the field of brain tumor detection. It has the potential to assist healthcare professionals in making faster and more accurate diagnoses, leading to improved patient care and outcomes. The integration of AI into medical diagnostics has immense potential in revolutionizing brain tumor detection and positively impacting the lives of patients around the world.