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dc.contributor.authorSun, Wanxin
dc.contributor.authorChang, Shi
dc.contributor.authorTai, Dean C. S.
dc.contributor.authorTan, Nancy
dc.contributor.authorXiao, Guangfa
dc.contributor.authorTang, Huihuan
dc.contributor.authorYu, Hanry
dc.date.accessioned2012-02-16T17:48:34Z
dc.date.available2012-02-16T17:48:34Z
dc.date.issued2008-12
dc.date.submitted2008-07
dc.identifier.issn1083-3668
dc.identifier.issn1560-2281
dc.identifier.urihttp://hdl.handle.net/1721.1/69125
dc.description.abstractLiver fibrosis is associated with an abnormal increase in an extracellular matrix in chronic liver diseases. Quantitative characterization of fibrillar collagen in intact tissue is essential for both fibrosis studies and clinical applications. Commonly used methods, histological staining followed by either semiquantitative or computerized image analysis, have limited sensitivity, accuracy, and operator-dependent variations. The fibrillar collagen in sinusoids of normal livers could be observed through second-harmonic generation (SHG) microscopy. The two-photon excited fluorescence (TPEF) images, recorded simultaneously with SHG, clearly revealed the hepatocyte morphology. We have systematically optimized the parameters for the quantitative SHG/TPEF imaging of liver tissue and developed fully automated image analysis algorithms to extract the information of collagen changes and cell necrosis. Subtle changes in the distribution and amount of collagen and cell morphology are quantitatively characterized in SHG/TPEF images. By comparing to traditional staining, such as Masson’s trichrome and Sirius red, SHG/TPEF is a sensitive quantitative tool for automated collagen characterization in liver tissue. Our system allows for enhanced detection and quantification of sinusoidal collagen fibers in fibrosis research and clinical diagnostics.en_US
dc.description.sponsorshipInstitute of Bioengineering and Nanotechnology (Singapore)en_US
dc.description.sponsorshipSingapore. Biomedical Research Council (Grant No. R185-001-045-305)en_US
dc.description.sponsorshipSingapore. Agency for Science, Technology and Researchen_US
dc.description.sponsorshipSingapore. Ministry of Education (Grant No. R-185- 000-135-112)en_US
dc.description.sponsorshipSingapore. National Medical Research Council (Grant No. R-185-000-099- 213)en_US
dc.description.sponsorshipSingapore-MIT Alliance Computational and Systems Biology Flagship Projecten_US
dc.description.sponsorshipExxon Mobil Corporation (ExxonMobil–NUS Clinician Fellowship Award)en_US
dc.language.isoen_US
dc.publisherSPIE - International Society for Optical Engineeringen_US
dc.relation.isversionofhttp://dx.doi.org/10.1117/1.3041159en_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.titleNonlinear optical microscopy: use of second harmonic generation and two-photon microscopy for automated quantitative liver fibrosis studiesen_US
dc.typeArticleen_US
dc.identifier.citationSun, Wanxin et al. “Nonlinear Optical Microscopy: Use of Second Harmonic Generation and Two-photon Microscopy for Automated Quantitative Liver Fibrosis Studies.” Journal of Biomedical Optics 13.6 (2008): 064010. Web. 16 Feb. 2012. © 2008 SPIE - International Society for Optical Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.approverYu, Hanry
dc.contributor.mitauthorYu, Hanry
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.orderedauthorsSun, Wanxin; Chang, Shi; Tai, Dean C. S.; Tan, Nancy; Xiao, Guangfa; Tang, Huihuan; Yu, Hanryen
dc.identifier.orcidhttps://orcid.org/0000-0002-0339-3685
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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