首页|基于多模态影像的脑龄预测模型与应用

基于多模态影像的脑龄预测模型与应用

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脑龄预测是借助脑影像数据进行建模与分析,客观评估大脑成熟与老化程度的一种分析技术.随着人工智能算法的发展,脑龄预测的相关研究近年呈现快速增长态势.已有研究普遍认为脑龄预测有助于评估大脑的健康状态,是监测大脑异常发育和老化的有效指标,具有预测大脑异常老化和病变发生的巨大潜力.针对近年来脑龄预测领域的发展,从脑龄分类、脑龄模型及其临床应用等几方面,综述该领域的最新研究进展,并进一步概述脑龄研究未来发展的挑战和趋势.
Brain Age Prediction Methods and Applications Based on Multimodal Neuroimaging Data
Brain age can predict the degree of brain maturity and aging by modeling and analysis of neuroimaging data.With the development of artificial intelligence algorithms,the related research on brain age prediction have demonstrated a rapid emerging trend.It is generally recognized that brain age can be an effective biomarker for monitoring abnormal development and aging,which can assess individual brain health,and has great potential to detect abnormal aging and disease.In the context of rapid growing of research interests on the brain age prediction,this review summarized the latest achievements from the aspects of brain age classification,brain age model,clinical application,and further discusses challenges and developing directions of brain age in the future studies.

neuroimaging databrain agepredicted age differencedeep learning

刘爽、俞婧、陈元园、范秋筠、赵欣、明东

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天津大学医学工程与转化医学研究院,天津 300072

天津市脑科学中心,天津 300072

天津大学精密仪器与光电子工程学院,天津 300072

神经影像 脑龄 脑龄预测偏差 深度学习

国家自然科学基金国家自然科学基金

8192502082071994

2024

中国生物医学工程学报
中国生物医学工程学会

中国生物医学工程学报

CSTPCD北大核心
影响因子:0.614
ISSN:0258-8021
年,卷(期):2024.43(1)
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