| 影像与基因特征分析方法在阿尔茨海默病中的研究进展 |
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| 引用本文： | 韩立婷,姚旭峰,金宇,赵从义,黄钢.影像与基因特征分析方法在阿尔茨海默病中的研究进展[J].中国生物医学工程学报,2022,41(4):485-492. |
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| 作者姓名： | 韩立婷 姚旭峰 金宇 赵从义 黄钢 |
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| 作者单位： | 1(上海理工大学医疗器械与食品学院,上海 200082)2(上海健康医学院医学影像学院,上海 201308)3(上海市分子影像学重点实验室,上海健康医学院,上海 201308) |
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| 基金项目： | 国家自然科学基金(61971275);国家自然科学基金重点项目(81830052) |
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| 摘 要： | 阿尔茨海默病(AD)是一种最常见的神经退行性疾病,且已有研究证实其表型易受遗传因素的影响。近年来,随着多模态脑成像和高通量基因组学在医学影像中广泛应用,通过数据挖掘、数学建模等方法,探索影像与基因的关联分析已成为新的热点。目前,用影像与基因特征联合分析来研究AD,并在AD的早期诊断、分类和预后分析等方面该技术的应用已经取得了重大的进展。首先对影像与基因特征分析技术进行概述,然后阐述了统计学及机器学习方法在影像与基因特征联合分析中的应用,最后对该技术的发展前景进行了展望。
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| 关 键 词： | 影像与基因特征 阿尔茨海默病 机器学习 统计学方法 深度学习 |
| 收稿时间： | 2020-10-09 |
Research Progress for the Analysis of Images and Genetic Features in Alzheimer′s Disease |
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| Han Liting,Yao Xufeng,Jin Yu,Zhao Congyi,Huang Gang.Research Progress for the Analysis of Images and Genetic Features in Alzheimer′s Disease[J].Chinese Journal of Biomedical Engineering,2022,41(4):485-492. |
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| Authors: | Han Liting Yao Xufeng Jin Yu Zhao Congyi Huang Gang |
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| Institution: | (School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200082, China) (College of Medical Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201308, China) (Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201308, China) |
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| Abstract: | Alzheimer′s disease (AD) is one of the most common neurodegenerative diseases, and its phenotype has shown susceptible to genetic factors. In recent years, with the wide application of multimodal brain imaging and high-throughput genomics in medical imaging, it has become a new hotspot to explore the association analysis between images and genes by means of data mining and mathematical modeling. Till now, the combined analysis of images and genetic characteristics has been used to study AD and has made significant progress in the early diagnosis, classification, and prognostic analysis. This article first summarized the imaging and genetic features, then explained the application of statistics and machine learning (ML) methods in the joint analysis of image gene features, and finally summarized and proposed its development perspectives. |
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| Keywords: | imaging and genetic features Alzheimer′s disease machine learning statistical methods deep learning |
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