Multi-source multi-target dictionary learning for prediction of cognitive decline

Jie Zhang, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations


Alzheimer’s Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine presymptomatic AD subjects and enable early intervention. Recently, Multitask sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information. To address these challenges, we formulate an unsupervised framework for multi-task sparse feature learning based on a novel dictionary learning algorithm. To solve the unsupervised learning problem, we propose a two-stage Multi-Source Multi-Target Dictionary Learning (MMDL) algorithm. In stage 1, we propose a multi-source dictionary learning method to utilize the common and individual sparse features in different time slots. In stage 2, supported by a rigorous theoretical analysis, we develop a multi-task learning method to solve the missing label problem. Empirical studies on an N = 3970 longitudinal brain image data set, which involves 2 sources and 5 targets, demonstrate the improved prediction accuracy and speed efficiency of MMDL in comparison with other state-of-the-art algorithms.

Original languageEnglish
Title of host publicationInformation Processing in Medical Imaging - 25th International Conference, IPMI 2017, Proceedings
EditorsHongtu Zhu, Marc Niethammer, Martin Styner, Hongtu Zhu, Dinggang Shen, Pew-Thian Yap, Stephen Aylward, Ipek Oguz
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783319590493
StatePublished - 2017
Externally publishedYes
Event25th International Conference on Information Processing in Medical Imaging, IPMI 2017 - Boone, United States
Duration: 25 Jun 201730 Jun 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10265 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference25th International Conference on Information Processing in Medical Imaging, IPMI 2017
Country/TerritoryUnited States


  • Alzheimer’s disease
  • Dictionary learning
  • Multi-task


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