Spatially Weighted Principal Component Analysis for Imaging Classification.

TitleSpatially Weighted Principal Component Analysis for Imaging Classification.
Publication TypeJournal Article
Year of Publication2015
AuthorsGuo, Ruixin, Mihye Ahn, and Hongtu Zhu
Corporate AuthorsAlzheimer's Disease Neuroimaging Initiative
JournalJ Comput Graph Stat
Volume24
Issue1
Pagination274-296
Date Published2015 Jan
ISSN1061-8600
Abstract

The aim of this paper is to develop a supervised dimension reduction framework, called Spatially Weighted Principal Component Analysis (SWPCA), for high dimensional imaging classification. Two main challenges in imaging classification are the high dimensionality of the feature space and the complex spatial structure of imaging data. In SWPCA, we introduce two sets of novel weights including global and local spatial weights, which enable a selective treatment of individual features and incorporation of the spatial structure of imaging data and class label information. We develop an e cient two-stage iterative SWPCA algorithm and its penalized version along with the associated weight determination. We use both simulation studies and real data analysis to evaluate the finite-sample performance of our SWPCA. The results show that SWPCA outperforms several competing principal component analysis (PCA) methods, such as supervised PCA (SPCA), and other competing methods, such as sparse discriminant analysis (SDA).

DOI10.1080/10618600.2014.912135
Alternate JournalJ Comput Graph Stat
Original PublicationSpatially weighted principal component analysis for imaging classification.
PubMed ID26089629
PubMed Central IDPMC4467033
Grant ListUL1 TR001111 / TR / NCATS NIH HHS / United States
U01 AG024904 / AG / NIA NIH HHS / United States
KL2 TR001080 / TR / NCATS NIH HHS / United States
UL1 TR002489 / TR / NCATS NIH HHS / United States
TL1 TR001081 / TR / NCATS NIH HHS / United States
R01 MH086633 / MH / NIMH NIH HHS / United States
UL1 TR001082 / TR / NCATS NIH HHS / United States
UL1 RR025747 / RR / NCRR NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
R01 CA074015 / CA / NCI NIH HHS / United States