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山东大学学报 (医学版) ›› 2020, Vol. 58 ›› Issue (8): 14-21.doi: 10.6040/j.issn.1671-7554.0.2019.1503

• 脑科学与类脑智能研究专题 • 上一篇    下一篇

阿尔兹海默病的智能诊断方法

尹义龙1,*(),袭肖明2,孟宪静3   

  1. 1. 山东大学软件学院机器学习与数据挖掘实验室，山东 济南250101
    2. 山东建筑大学计算机科学与技术学院，山东 济南 250101
    3. 山东财经大学计算机科学与技术学院，山东 济南 250014
  • 收稿日期:2019-12-27 出版日期:2020-08-07 发布日期:2020-08-07
  • 通讯作者: 尹义龙 E-mail:ylyin@sdu.edu.cn
  • 作者简介:尹义龙，教授、博士研究生导师，主要从事人工智能、机器学习、数据挖掘领域的研究工作。现担任中国计算机学会人工智能与模式识别专委会常委、副秘书长，中国人工智能学会机器学习专委会常委、副秘书长，山东省人工智能学会理事长，山东省大数据研究会副会长等学术兼职。入选教育部新世纪优秀人才支持计划，获得山东省自然科学杰出青年基金资助。主持国家自然科学基金重点项目1项，国家重点研发专项课题1项、面上项目3项、青年项目1项，主持省部级科研项目11项。在《IEEE Trans Knowl Data En》《IEEE Trans Image Processing》《Pattern Recogn 》《IEEE Trans Multimedia》等国际期刊和AAAI、IJCAI、CVPR、MM、SIGIR、IPMI、MICCAI等国际会议发表论文80余篇。获山东省科技进步二等奖2项(第一完成人)。
  • 基金资助:
    国家自然科学基金(61876098);国家自然科学基金(61701280);国家自然科学基金(61801263);国家重点研发专项计划(2018YFC0830102)

Intelligent diagnosis methods of Alzheimer's disease

Yilong YIN1,*(),Xiaoming XI2,Xianjing MENG3   

  1. 1. MLA Lab in School of Software, Shandong University, Jinan 250101, Shandong, China
    2. School of Computer Science and Technology, Shandong Jianzhu University, Jinan 250101, Shandong, China
    3. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan 250014, Shandong, China
  • Received:2019-12-27 Online:2020-08-07 Published:2020-08-07
  • Contact: Yilong YIN E-mail:ylyin@sdu.edu.cn

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摘要：

随着人口老龄化的日渐严重，阿尔兹海默病(AD)的相关研究已成为重要的公共卫生课题。然而，目前尚无药物能够治愈AD，早发现、早治疗有助于延缓该疾病的发展。在众多的AD辅助诊断工具中，神经影像对于AD的早期诊断具有重要作用，已成为一个热门的研究课题。对基于神经影像的AD智能诊断方法进行综述，从基于单模态影像的智能AD诊断和多模态融合的智能AD诊断两方面对现有方法进行了分析，并对未来的研究方向进行了展望，有利于为AD的诊断提供新观点和新思路。

关键词: 阿尔兹海默病, 神经影像, 智能诊断

Abstract:

As the number of elderly people increases, Alzheimer's disease (AD) has become a tremendous economic and societal burden. The research on AD has been considered an important global public health topic. However, there is currently no cure for AD; therefore, early detection is very helpful for the diagnosis. Neuroimaging plays an important role for the early diagnosis of AD among all detection tools and has attracted great attention in recent years. In order to provide new insights into the intelligent diagnosis methods of AD, this paper reviews the recent advances including methods based on single-modality and multi-modality and discusses the future work.

Key words: Alzheimer's disease, Neuroimaging, Intelligent diagnosis

中图分类号: 

  • R574

表1

现有AD诊断数据库简介"

数据库 包含模态 包含分组
ADNI MRI、PET、生物标记、临床评估分值等 NC、MCI、AD
OASIS MRI NC、轻中度AD
MIRIAD MRI、MMSE等 NC、轻中度AD
AIBL PET、CSF NC、MCI、AD

图1

现有AD诊断方法分类"

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