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dc.contributor.authorSeo, Jihye
dc.contributor.authorAn, Yuri
dc.contributor.authorLee, Jungsul
dc.contributor.authorKu, Taeyun
dc.contributor.authorKang, Yujung
dc.contributor.authorAhn, Chulwoo
dc.contributor.authorChoi, Chulhee
dc.date.accessioned2016-07-07T15:17:07Z
dc.date.available2016-07-07T15:17:07Z
dc.date.issued2016-04
dc.date.submitted2016-01
dc.identifier.issn1083-3668
dc.identifier.urihttp://hdl.handle.net/1721.1/103534
dc.description.abstractIndocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.en_US
dc.description.sponsorshipNational Research Foundation of Korea (Bio & Medical Technology Development Program, Korean government funding, MSIP (No. 2011-0019697)en_US
dc.language.isoen_US
dc.publisherSPIEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1117/1.jbo.21.4.046003en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceSPIEen_US
dc.titlePrincipal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathyen_US
dc.typeArticleen_US
dc.identifier.citationSeo, Jihye, Yuri An, Jungsul Lee, Taeyun Ku, Yujung Kang, Chulwoo Ahn, and Chulhee Choi. “Principal Component Analysis of Dynamic Fluorescence Images for Diagnosis of Diabetic Vasculopathy.” Journal of Biomedical Optics 21, no. 4 (April 12, 2016): 046003.en_US
dc.contributor.departmentInstitute for Medical Engineering and Scienceen_US
dc.contributor.mitauthorKu, Taeyunen_US
dc.relation.journalJournal of Biomedical Opticsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsSeo, Jihye; An, Yuri; Lee, Jungsul; Ku, Taeyun; Kang, Yujung; Ahn, Chulwoo; Choi, Chulheeen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-9447-7579
mit.licensePUBLISHER_POLICYen_US


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