摘要
阿尔兹海默症(AD)是一种进行性且不可逆的神经退行性疾病,随着脑细胞逐渐退化,认知能力逐步下降,最终可能导致死亡。在AD的诊断过程中,早期识别与干预是至关重要的。近年来,深度学习进一步推动AD影像分类方法的发展,并促进深度模型在临床早期诊断AD中的应用。为临床实现精确的早期诊断进而对AD患者进行分类,研究者结合深度学习和MRI成像,提供更加精确的模型。本文对国内外相关文献进行分析和总结,介绍AD常用的公开数据集和评价标准,分析MRI成像在AD分类中的应用及其与深度学习方法的融合,重点对CNN、迁移学习、注意力机制和多模态等技术在AD分类中的应用进行整理分析,讨论深度学习在AD分类应用中的优缺点及发展趋势,旨在为深度学习在AD领域的应用研究开辟新的思路。
Alzheimer's disease(AD)is a progressive,irreversible neurodegenerative disorder characterized by gradual brain cell degeneration,leading to progressive decline in cognitive function and ultimately death.Early identification and intervention are critical to AD diagnosis.In recent years,deep learning has further advanced image-based AD classification methods and facilitated the application of deep models in the early AD diagnosis.To achieve accurate early diagnosis and subsequent classification of AD,researchers have integrated deep learning with magnetic resonance imaging to develop more precise models.By analyzing and synthesizing relevant domestic and international literature,this review introduces commonly used public datasets and evaluation criteria for AD,analyzes the application of magnetic resonance imaging in AD classification and its integration with deep learning methods,and highlights the roles of techniques such as convolutional neural networks,transfer learning,attention mechanisms,and multimodal approaches in AD classification.It also discusses the advantages,limitations,and developmental trends of deep learning in AD classification,aiming to provide new insights for the application of deep learning inAD research.
作者
公丕强
闫作剑
李雪
林冬梅
陈扶明
GONG Piqiang;YAN Zuojian;LI Xue;LIN Dongmei;CHEN Fuming(School of Medical Information Engineering,Gansu University of Chinese Medicine,Lanzhou 730000,China;Department of Engineering,the 940th Hospital of Joint Logistics Support Force of Chinese People's Liberation Army,Lanzhou 730050,China;College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China)
出处
《中国医学物理学杂志》
2025年第11期1420-1433,共14页
Chinese Journal of Medical Physics
基金
国家自然科学基金(61901515)
甘肃省自然科学基金(22JR5RA002)。
关键词
阿尔兹海默症
深度学习
磁共振成像
神经影像
综述
Alzheimer's disease
deep learning
magnetic resonance imaging
neuroimaging
review
