Multiresolution Localization with Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence

Bentz, Brian Z.; Lin, Dergan; Patel, Justin A.; Webb, Kevin J.

doi:10.1109/TIP.2019.2931080

Title: Multiresolution Localization with Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence

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Abstract

A super-resolution optical imaging method is introduced that relies on the distinct temporal information associated with each fluorescent optical reporter to determine its spatial position to high precision with measurements of heavily scattered light. This multiple-emitter localization approach uses a diffusion equation forward model in a cost function, and has the potential to achieve micron-scale spatial resolution through centimeters of tissue. Utilizing some degree of temporal separation for the reporter emissions, position and emission strength are determined using a computationally efficient time stripping multiresolution algorithm. The method circumvents the spatial resolution challenges faced by earlier optical imaging approaches using a diffusion equation forward model, and is promising for in vivo applications. For example, in principle, the approach could be used to localize individual neurons firing throughout a rodent brain, enabling direct imaging of neural network activity.

Authors:

Bentz, Brian Z. ^[1]; Lin, Dergan ^[2]; Patel, Justin A. ^[2]; Webb, Kevin J. ^[2]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Purdue Univ., West Lafayette, IN (United States)

Publication Date:: Mon Aug 12 00:00:00 EDT 2019

Research Org.:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA); National Science Foundation (NSF); National Institutes of Health (NIH)

OSTI Identifier:: 1559546

Report Number(s):: SAND-2018-10834J
Journal ID: ISSN 1057-7149; 668347

Grant/Contract Number:: AC04-94AL85000

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Image Processing

Additional Journal Information:: Journal Volume: 29; Journal ID: ISSN 1057-7149

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 42 ENGINEERING; Super-resolution; optical imaging; turbid media; localization; fluorescence; matching pursuit

Citation Formats


                    Bentz, Brian Z., Lin, Dergan, Patel, Justin A., and Webb, Kevin J. Multiresolution Localization with Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence.  United States: N. p., 2019. 
Web.  doi:10.1109/TIP.2019.2931080.

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                    Bentz, Brian Z., Lin, Dergan, Patel, Justin A., & Webb, Kevin J. Multiresolution Localization with Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence.  United States.  https://doi.org/10.1109/TIP.2019.2931080

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                    Bentz, Brian Z., Lin, Dergan, Patel, Justin A., and Webb, Kevin J. Mon .  
"Multiresolution Localization with Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence".  United States.  https://doi.org/10.1109/TIP.2019.2931080.  https://www.osti.gov/servlets/purl/1559546.

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@article{osti_1559546,

  title        = {Multiresolution Localization with Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence},

  author       = {Bentz, Brian Z. and Lin, Dergan and Patel, Justin A. and Webb, Kevin J.},

  abstractNote = {A super-resolution optical imaging method is introduced that relies on the distinct temporal information associated with each fluorescent optical reporter to determine its spatial position to high precision with measurements of heavily scattered light. This multiple-emitter localization approach uses a diffusion equation forward model in a cost function, and has the potential to achieve micron-scale spatial resolution through centimeters of tissue. Utilizing some degree of temporal separation for the reporter emissions, position and emission strength are determined using a computationally efficient time stripping multiresolution algorithm. The method circumvents the spatial resolution challenges faced by earlier optical imaging approaches using a diffusion equation forward model, and is promising for in vivo applications. For example, in principle, the approach could be used to localize individual neurons firing throughout a rodent brain, enabling direct imaging of neural network activity.},

  doi          = {10.1109/TIP.2019.2931080},

  journal      = {IEEE Transactions on Image Processing},

  number       = ,

  volume       = 29,

  place        = {United States},

  year         = {Mon Aug 12 00:00:00 EDT 2019},

  month        = {Mon Aug 12 00:00:00 EDT 2019}

}

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