Detection of Brain Tumor Severity from MRI Images using Machine Learning

Abstract

The progress in medical imaging technology, including Magnetic Resonance Imaging (MRI), has greatly aided in the prompt identification and diagnosis of brain cancers. This study article provides a comprehensive examination of the use of machine learning methods to evaluate the seriousness of brain tumors using MRI images. The project seeks to assess the latest approaches, problems, and prospects in using machine learning algorithms to improve the precision and effectiveness of tumor severity diagnosis. The review involves a comprehensive examination of several machine learning techniques, encompassing both conventional methods and current breakthroughs like deep learning models, within the specific context of evaluating the severity of brain tumors. The study investigates the use of several strategies for extracting features, preprocessing data, and using classification algorithms to distinguish between benign and malignant tumors. In addition, the research examines the combination of many types of imaging data and the inclusion of clinical information to enhance the overall prediction accuracy. In addition, this study presents a thorough analysis of the current datasets, benchmarking methods, and assessment criteria to offer valuable insights into the dependability and applicability of the suggested models. The article discusses the difficulties related to having a restricted number of annotated datasets, the comprehensibility of intricate models, and the moral concerns when implementing machine learning in healthcare environments. The survey ends with a discussion on possible future research approaches, highlighting the need for joint endeavors among medical practitioners, image analysts, and machine learning specialists to create strong and practical models for clinical use. The results of this study are anticipated to aid in the progress of medical image analysis and promote the creation of more precise and dependable methods for identifying and describing brain cancers.