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Conference Paper: Broadband hyperspectral coherent anti-Stokes Raman scattering microscopy for stain-free histological imaging with principal component analysis

TitleBroadband hyperspectral coherent anti-Stokes Raman scattering microscopy for stain-free histological imaging with principal component analysis
Authors
Issue Date2014
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xml?WT.svl=mddp2
Citation
Conference 8948 - Multiphoton Microscopy in the Biomedical Sciences XIV, San Francisco, California, USA, 2-4 February 2014. In Proceedings of SPIE - International Society for Optical Engineering, 2014, v. 8948, p. article no. 89480R How to Cite?
AbstractRoutine procedures in standard histopathology involve laborious steps of tissue processing and staining for final examination. New techniques which can bypass these procedures and thus minimize the tissue handling error would be of great clinical value. Coherent anti-Stokes Raman scattering (CARS) microscopy is an attractive tool for label-free biochemical-specific characterization of biological specimen. However, a vast majority of prior works on CARS (or stimulated Raman scattering (SRS)) bioimaging restricted analyses on a narrowband or well-distinctive Raman spectral signatures. Although hyperspectral SRS/CARS imaging has recently emerged as a better solution to access wider-band spectral information in the image, studies mostly focused on a limited spectral range, e.g. CH-stretching vibration of lipids, or non-biological samples. Hyperspectral image information in the congested fingerprint spectrum generally remains untapped for biological samples. In this regard, we further explore ultrabroadband hyperspectral multiplex (HM-CARS) to perform chemoselective histological imaging with the goal of exploring its utility in stain-free clinical histopathology. Using the supercontinuum Stokes, our system can access the CARS spectral window as wide as >2000cm-1. In order to unravel the congested CARS spectra particularly in the fingerprint region, we first employ a spectral phase-retrieval algorithm based on Kramers–Kronig (KK) transform to minimize the non-resonant background in the CARS spectrum. We then apply principal component analysis (PCA) to identify and map the spatial distribution of different biochemical components in the tissues. We demonstrate chemoselective HM-CARS imaging of a colon tissue section which displays the key cellular structures that correspond well with standard stained-tissue observation. © 2014 SPIE.
Persistent Identifierhttp://hdl.handle.net/10722/204011
ISBN
ISSN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, Jen_US
dc.contributor.authorGuo, Ben_US
dc.contributor.authorWong, KKYen_US
dc.contributor.authorTsia, KKMen_US
dc.date.accessioned2014-09-19T20:01:37Z-
dc.date.available2014-09-19T20:01:37Z-
dc.date.issued2014en_US
dc.identifier.citationConference 8948 - Multiphoton Microscopy in the Biomedical Sciences XIV, San Francisco, California, USA, 2-4 February 2014. In Proceedings of SPIE - International Society for Optical Engineering, 2014, v. 8948, p. article no. 89480Ren_US
dc.identifier.isbn9780819498618-
dc.identifier.issn0277-786X-
dc.identifier.urihttp://hdl.handle.net/10722/204011-
dc.description.abstractRoutine procedures in standard histopathology involve laborious steps of tissue processing and staining for final examination. New techniques which can bypass these procedures and thus minimize the tissue handling error would be of great clinical value. Coherent anti-Stokes Raman scattering (CARS) microscopy is an attractive tool for label-free biochemical-specific characterization of biological specimen. However, a vast majority of prior works on CARS (or stimulated Raman scattering (SRS)) bioimaging restricted analyses on a narrowband or well-distinctive Raman spectral signatures. Although hyperspectral SRS/CARS imaging has recently emerged as a better solution to access wider-band spectral information in the image, studies mostly focused on a limited spectral range, e.g. CH-stretching vibration of lipids, or non-biological samples. Hyperspectral image information in the congested fingerprint spectrum generally remains untapped for biological samples. In this regard, we further explore ultrabroadband hyperspectral multiplex (HM-CARS) to perform chemoselective histological imaging with the goal of exploring its utility in stain-free clinical histopathology. Using the supercontinuum Stokes, our system can access the CARS spectral window as wide as >2000cm-1. In order to unravel the congested CARS spectra particularly in the fingerprint region, we first employ a spectral phase-retrieval algorithm based on Kramers–Kronig (KK) transform to minimize the non-resonant background in the CARS spectrum. We then apply principal component analysis (PCA) to identify and map the spatial distribution of different biochemical components in the tissues. We demonstrate chemoselective HM-CARS imaging of a colon tissue section which displays the key cellular structures that correspond well with standard stained-tissue observation. © 2014 SPIE.-
dc.languageengen_US
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xml?WT.svl=mddp2-
dc.relation.ispartofProceedings of SPIE - International Society for Optical Engineeringen_US
dc.rightsProceedings of SPIE - International Society for Optical Engineering. Copyright © S P I E - International Society for Optical Engineering.-
dc.rightsCopyright notice format: Copyright 2014 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleBroadband hyperspectral coherent anti-Stokes Raman scattering microscopy for stain-free histological imaging with principal component analysisen_US
dc.typeConference_Paperen_US
dc.identifier.emailGuo, B: bsguo@hku.hken_US
dc.identifier.emailWong, KKY: kywong04@hkucc.hku.hken_US
dc.identifier.emailTsia, KKM: tsia@hku.hken_US
dc.identifier.authorityWong, KKY=rp00189en_US
dc.identifier.authorityTsia, KKM=rp01389en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1117/12.2039215-
dc.identifier.scopuseid_2-s2.0-84898025258-
dc.identifier.hkuros236210en_US
dc.identifier.hkuros240554-
dc.identifier.volume8948-
dc.identifier.isiWOS:000336743000010-
dc.publisher.placeUnited States-

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