Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review

IF 17.2 1区 工程技术 Q1 ENGINEERING, BIOMEDICAL
Toufique A. Soomro;Lihong Zheng;Ahmed J. Afifi;Ahmed Ali;Shafiullah Soomro;Ming Yin;Junbin Gao
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引用次数: 40

Abstract

Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain disease and monitor treatment as non-invasive imaging technology. MRI produces three-dimensional images that help neurologists to identify anomalies from brain images precisely. However, this is a time-consuming and labor-intensive process. The improvement in machine learning and efficient computation provides a computer-aid solution to analyze MRI images and identify the abnormality quickly and accurately. Image segmentation has become a hot and research-oriented area in the medical image analysis community. The computer-aid system for brain abnormalities identification provides the possibility for quickly classifying the disease for early treatment. This article presents a review of the research papers (from 1998 to 2020) on brain tumors segmentation from MRI images. We examined the core segmentation algorithms of each research paper in detail. This article provides readers with a complete overview of the topic and new dimensions of how numerous machine learning and image segmentation approaches are applied to identify brain tumors. By comparing the state-of-the-art and new cutting-edge methods, the deep learning methods are more effective for the segmentation of the tumor from MRI images of the brain.
基于机器学习的MR脑肿瘤图像分割研究综述
磁共振成像(MRI)作为一种非侵入性成像技术,已被广泛用于检测和诊断脑部疾病以及监测治疗。MRI产生三维图像,帮助神经学家从大脑图像中准确识别异常。然而,这是一个耗时耗力的过程。机器学习和高效计算的改进为快速准确地分析MRI图像和识别异常提供了计算机辅助解决方案。图像分割已经成为医学图像分析界的一个热点和研究方向。用于大脑异常识别的计算机辅助系统为快速分类疾病以进行早期治疗提供了可能性。本文综述了1998年至2020年关于从MRI图像中分割脑肿瘤的研究论文。我们详细检查了每篇研究论文的核心分割算法。这篇文章为读者提供了一个完整的主题概述,以及许多机器学习和图像分割方法如何应用于识别脑肿瘤的新维度。通过比较最先进和最新的尖端方法,深度学习方法对于从大脑的MRI图像中分割肿瘤更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Reviews in Biomedical Engineering
IEEE Reviews in Biomedical Engineering Engineering-Biomedical Engineering
CiteScore
31.70
自引率
0.60%
发文量
93
期刊介绍: IEEE Reviews in Biomedical Engineering (RBME) serves as a platform to review the state-of-the-art and trends in the interdisciplinary field of biomedical engineering, which encompasses engineering, life sciences, and medicine. The journal aims to consolidate research and reviews for members of all IEEE societies interested in biomedical engineering. Recognizing the demand for comprehensive reviews among authors of various IEEE journals, RBME addresses this need by receiving, reviewing, and publishing scholarly works under one umbrella. It covers a broad spectrum, from historical to modern developments in biomedical engineering and the integration of technologies from various IEEE societies into the life sciences and medicine.
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