{"title":"神经成像驱动的大脑年龄估计用于识别大脑疾病和健康状况的研究进展","authors":"Shiwangi Mishra;Iman Beheshti;Pritee Khanna","doi":"10.1109/RBME.2021.3107372","DOIUrl":null,"url":null,"abstract":"<italic>Background:</i>\n Neuroimage analysis has made it possible to perform various anatomical analyses of the brain regions and helps detect different brain conditions/ disorders. Recently, neuroimaging-driven estimation of brain age is introduced as a robust biomarker for detecting different diseases and health conditions. \n<italic>Objective:</i>\n To present a comprehensive review of brain age frameworks concerning: i) designing view: an overview of brain age frameworks based on image modality and methods used, and ii) clinical aspect: an overview of the application of brain age frameworks for detection of neurological disorders or health conditions. \n<italic>Methods:</i>\n PubMed is explored to collect 136 articles from January 2010 to June 2021 using “Brain Age Estimation” and “Brain Imaging,” along with combinations of other radiological terms. \n<italic>Results & Conclusion:</i>\n The studies presented in this review are evidence of using brain age estimation methods in detecting various brain diseases/conditions. The survey also highlights tools and methods for brain age estimation and addresses some future research directions.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"371-385"},"PeriodicalIF":17.2000,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"A Review of Neuroimaging-Driven Brain Age Estimation for Identification of Brain Disorders and Health Conditions\",\"authors\":\"Shiwangi Mishra;Iman Beheshti;Pritee Khanna\",\"doi\":\"10.1109/RBME.2021.3107372\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<italic>Background:</i>\\n Neuroimage analysis has made it possible to perform various anatomical analyses of the brain regions and helps detect different brain conditions/ disorders. Recently, neuroimaging-driven estimation of brain age is introduced as a robust biomarker for detecting different diseases and health conditions. \\n<italic>Objective:</i>\\n To present a comprehensive review of brain age frameworks concerning: i) designing view: an overview of brain age frameworks based on image modality and methods used, and ii) clinical aspect: an overview of the application of brain age frameworks for detection of neurological disorders or health conditions. \\n<italic>Methods:</i>\\n PubMed is explored to collect 136 articles from January 2010 to June 2021 using “Brain Age Estimation” and “Brain Imaging,” along with combinations of other radiological terms. \\n<italic>Results & Conclusion:</i>\\n The studies presented in this review are evidence of using brain age estimation methods in detecting various brain diseases/conditions. The survey also highlights tools and methods for brain age estimation and addresses some future research directions.\",\"PeriodicalId\":39235,\"journal\":{\"name\":\"IEEE Reviews in Biomedical Engineering\",\"volume\":\"16 \",\"pages\":\"371-385\"},\"PeriodicalIF\":17.2000,\"publicationDate\":\"2021-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Reviews in Biomedical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/9521711/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Reviews in Biomedical Engineering","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/9521711/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
A Review of Neuroimaging-Driven Brain Age Estimation for Identification of Brain Disorders and Health Conditions
Background:
Neuroimage analysis has made it possible to perform various anatomical analyses of the brain regions and helps detect different brain conditions/ disorders. Recently, neuroimaging-driven estimation of brain age is introduced as a robust biomarker for detecting different diseases and health conditions.
Objective:
To present a comprehensive review of brain age frameworks concerning: i) designing view: an overview of brain age frameworks based on image modality and methods used, and ii) clinical aspect: an overview of the application of brain age frameworks for detection of neurological disorders or health conditions.
Methods:
PubMed is explored to collect 136 articles from January 2010 to June 2021 using “Brain Age Estimation” and “Brain Imaging,” along with combinations of other radiological terms.
Results & Conclusion:
The studies presented in this review are evidence of using brain age estimation methods in detecting various brain diseases/conditions. The survey also highlights tools and methods for brain age estimation and addresses some future research directions.
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.