Literature DB >> 19483906

High resolution, molecular-specific, reflectance imaging in optically dense tissue phantoms with structured-illumination.

Tomasz Tkaczyk, Mohammed Rahman, Vivian Mack, Konstantin Sokolov, Jeremy Rogers, Rebecca Richards-Kortum, Michael Descour.   

Abstract

Structured-illumination microscopy delivers confocal-imaging capabilities and may be used for optical sectioning in bio-imaging applications. However, previous structured-illumination implementations are not capable of imaging molecular changes within highly scattering, biological samples in reflectance mode. Here, we present two advances which enable successful structured illumination reflectance microscopy to image molecular changes in epithelial tissue phantoms. First, we present the sine approximation algorithm to improve the ability to reconstruct the in-focus plane when the out-of-focus light is much greater in magnitude. We characterize the dependencies of this algorithm on phase step error, random noise and backscattered out-of-focus contributions. Second, we utilize a molecular-specific reflectance contrast agent based on gold nanoparticles to label disease-related biomarkers and increase the signal and signal-to-noise ratio (SNR) in structured illumination microscopy of biological tissue. Imaging results for multi-layer epithelial cell phantoms with optical properties characteristic of normal and cancerous tissue labeled with nanoparticles targeted against the epidermal growth factor receptor (EGFR) are presented. Structured illumination images reconstructed with the sine approximation algorithm compare favorably to those obtained with a standard confocal microscope; this new technique can be implemented in simple and small imaging platforms for future clinical studies.

Entities:  

Year:  2004        PMID: 19483906     DOI: 10.1364/opex.12.003745

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  5 in total

1.  Optically-sectioned two-shot structured illumination microscopy with Hilbert-Huang processing.

Authors:  Krzysztof Patorski; Maciej Trusiak; Tomasz Tkaczyk
Journal:  Opt Express       Date:  2014-04-21       Impact factor: 3.894

2.  Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data.

Authors:  Sandra P Prieto; Keith K Lai; Jonathan A Laryea; Jason S Mizell; Timothy J Muldoon
Journal:  J Med Imaging (Bellingham)       Date:  2016-06-03

3.  Image restoration approach to address reduced modulation contrast in structured illumination microscopy.

Authors:  Nurmohammed Patwary; Ana Doblas; Chrysanthe Preza
Journal:  Biomed Opt Express       Date:  2018-03-13       Impact factor: 3.732

4.  Quantitative characterization of turbidity by radiative transfer based reflectance imaging.

Authors:  Peng Tian; Cheng Chen; Jiahong Jin; Heng Hong; Jun Q Lu; Xin-Hua Hu
Journal:  Biomed Opt Express       Date:  2018-04-04       Impact factor: 3.732

5.  Imaging performance of a miniature integrated microendoscope.

Authors:  Jeremy D Rogers; Sara Landau; Tomasz S Tkaczyk; Michael R Descour; Mohammed S Rahman; Rebecca Richards-Kortum; Ari H O Kärkäinen; Todd Christenson
Journal:  J Biomed Opt       Date:  2008 Sep-Oct       Impact factor: 3.170

  5 in total

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