用于轻度认知障碍诊断的群体相似约束功能脑网络建模方法

doi:10.11959/j.issn.2096-6652.201922

智能科学与技术学报 ›› 2019, Vol. 1 ›› Issue (2): 145-153.doi: 10.11959/j.issn.2096-6652.201922

用于轻度认知障碍诊断的群体相似约束功能脑网络建模方法

李伟凯¹,高欣²(),纪同俭³,王政霞¹()

¹ 南京航空航天大学计算机科学与技术学院，江苏南京 210016
² 上海全景医学影像诊断中心，上海 200233
³ 山东莒县妇幼保健医院，山东日照 276500

修回日期:2019-05-20 出版日期:2019-06-20 发布日期:2019-09-09
作者简介:李伟凯（1994- ），男，山东日照人，南京航空航天大学在读博士生，主要研究方向为医学图像处理、脑网络构建与分析。|高欣（1975- ），男，北京人，博士，副主任医师，上海市医学会结核病学专科分会委员、上海市中西医结合学会影像医学分会委员，主要研究方向为胸腹部肿瘤综合影像诊断、中枢神经系统磁共振诊断。|纪同俭（1972- ），男，山东日照人，主治医师，现任莒县妇幼保健计划生育服务中心理事长、莒县医学会秘书长、日照市医师协会理事，主要研究方向为普外科。|王政霞（1977- ），女，山东日照人，博士，重庆交通大学教授、硕士生导师，主要研究方向为机器学习、图像处理及医学影像诊断。
基金资助:
重庆市教委科技研究基金资助项目(KJQN201800716);重庆市教委科技研究基金资助项目(KJ175492);重庆市科委自然科学基金资助项目(2018jcyjAX0398);上海市卫计委科研课题基金资助项目(201740010)

Method of functional brain network modeling with group similarity constraint for mild cognitive impairment classification

Weikai LI¹,Xin GAO²(),Tongjian JI³,Zhengxia WANG¹()

¹ College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
² Shanghai Universal Medical Imaging Diagnostic Center,Shanghai 200233,China
³ Shandong Juxian Maternal and Child Health Hospital,Rizhao 276500,China

Revised:2019-05-20 Online:2019-06-20 Published:2019-09-09
Supported by:
Scientific and Technological Research Program of Chongqing Municipal Education Commission(KJQN201800716);Scientific and Technological Research Program of Chongqing Municipal Education Commission(KJ175492);Natural Science Foundation Project of CQCSTC(2018jcyjAX0398);Scientific Research Project of Shanghai Municipal Planning Commission of Health and Family Planing(201740010)

摘要/Abstract

摘要：

功能脑网络为理解大脑功能激活模式及大脑信息传递结构提供了一种有效的生物标记，如何更加有效地利用先验信息构建准确的脑网络模型尤为重要。提出了一种基于群体相似性约束的功能脑网络模型，通过引入张量低秩约束，利用张量的核范数，求解一个在组内具有低秩先验的脑网络组。这种方法利用组内的相似性约束，收缩脑网络的解空间，从而有效地构建更优的脑网络模型。将所构建的脑网络用于轻度认知障碍的判别任务，实验结果表明，所提出的基于群体相似性约束的脑网络建模方法，能够构建出更具判别性的脑网络，并得到了与以往研究一致的显著性连边，进一步验证了所提出方法的有效性。

关键词: 张量低秩, 大脑功能网络, 功能磁共振成像, 组约束

Abstract:

Functional brain network provides an effective biomarker for understanding brain activation patterns,the development of neurodegenerative diseases,and the structure of brain signaling.How to use priori information to build accurate brain network is particularly important in subsequent applications.A functional brain network construction model based on group similarity constraints was proposed.By introducing a tensor low rank constraint and using the nuclear norm of the tensor,a brain network group with a low rank prior in the group was solved.The group similarity constraints to shrink the solution space of the brain network was used,thus constructing a better functional brain network effectively.For evaluating the performance of the proposed method,the constructed brain network was adopted for the discriminative task of mild cognitive impairment.The experimental results show that the proposed functional brain network modeling method based on group similarity constraints can construct more discriminative brain network.In addition,based on the brain network constructed by the proposed method,the significant connections consistent with previous studies are obtained,and the effectiveness of the proposed method is further verified.

Key words: low-rank of tensor, functional brain network, functional magnetic resonance imaging, group constraint

中图分类号:

TP311.134.3

李伟凯, 高欣, 纪同俭, 等. 用于轻度认知障碍诊断的群体相似约束功能脑网络建模方法[J]. 智能科学与技术学报, 2019, 1(2): 145-153.

Weikai LI, Xin GAO, Tongjian JI, et al. Method of functional brain network modeling with group similarity constraint for mild cognitive impairment classification[J]. Chinese Journal of Intelligent Science and Technology, 2019, 1(2): 145-153.

图/表 4

参考文献 52

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方法	精度	敏感性	特异性
PC	68.61	71.01	66.17
PC+LR	75.91	79.71	72.05
SR	74.45	78.26	70.59
SR+LR	80.29	86.95	73.52

用于轻度认知障碍诊断的群体相似约束功能脑网络建模方法

Method of functional brain network modeling with group similarity constraint for mild cognitive impairment classification

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