Spatial Frequency Domain Imaging (SFDI) is a model-based, wide-field, non-contact method for measuring the absorption, scattering, and fluorescence properties of biological tissue. Optical properties are determined in each pixel simultaneously, by measuring the attenuation (or fluorescence) of sinusoidal patterns of light projected onto the sample at varying spatial frequencies and phases. The mean interrogation depth at a given wavelength is controlled by the spatial frequency of projection, and frequency-dependent differences in path length are used to calculate tissue optical properties using computational models. Images processed to extract SFDI images are recorded on a conventional camera system, which are costly and limited in data acquisition speed. The tissue properties recovered with SFDI vary with optical wavelength. Conventional camera systems are not able to resolve optical wavelengths, so SFDI imaging of the spectral variation in tissue properties would require switching illumination wavelengths and sequentially acquiring SFDI data. Alternatively, complex and expensive hyperspectral cameras can be used, but the cost is prohibitive for general clinical use. To overcome the limitations on SFDI image speed and to enable high speed hyperspectral SFDI imaging, we will develop the capability of SPatIal Frequency modulation for Imaging (SPIFI) to be used for SFDI image extraction with a broad optical spectrum. SPIFI exploits light modulated in space and time to encode spatial information into modulation frequency to that after illuminating an object, light collected on a single pixel detector can be decoded to form images. Single pixel detectors exhibit bandwidths many orders of magnitude larger than camera systems. The large detector bandwidth opens the capability for recording data for spatial and spectral information with a single photodetector that can be processed into hyperspectral images. The strategy of merging SPIFI, SFDI, and hyperspectral imaging will open up capabilities for unprecedented imaging rates of quantitative spectroscopic tissue imaging. In addition, modulation formats applied to the illumination light are adaptable - making single pixel hyperspectral SFDI an extremely agile imaging platform that can adapt the imaging, speed, resolution, and spectral resolution dynamically to optimize imaging conditions for specific target applications. The ability to adaptively optimize imaging of absorption, scattering, or florescence in tissues and build up depth-resolved hyperspectral images will open new capabilities for tissue imaging.

Public Health Relevance

These studies will allow us to adaptively and rapidly acquire data to develop and validate a new optical technology for real-time, quantitative hyperspectral imaging and depth sectioning of tissues light collected on a single pixel detector. By using high speed, inexpensive modulation platforms that apply spatial, spectral, and temporal modulation to an illumination beam, data for imaging absorption, scattering, and fluorescence from specimens across an optical spectrum will be obtained from a single photodetector. The technology has potential to replace conventional camera-based imaging and allow functional imaging of tissue properties. Our approach is expected to lead to new, bedside medical imaging methods for detecting disease, monitoring therapy response, and guiding surgical procedures.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21EB020953-02
Application #
9127237
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Shabestari, Behrouz
Project Start
2015-08-15
Project End
2017-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Colorado State University-Fort Collins
Department
Type
University-Wide
DUNS #
785979618
City
Fort Collins
State
CO
Country
United States
Zip Code
80523
Stockton, Patrick A; Field, Jeffrey J; Bartels, Randy A (2018) Single pixel quantitative phase imaging with spatial frequency projections. Methods 136:24-34
Torabzadeh, Mohammad; Park, Il-Yong; Bartels, Randy A et al. (2017) Compressed single pixel imaging in the spatial frequency domain. J Biomed Opt 22:30501