scholarly journals Spatial-Frequency Domain Imaging: An Emerging Depth-Varying and Wide-Field Technique for Optical Property Measurement of Biological Tissues

Photonics ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 162
Author(s):  
Zhizhong Sun ◽  
Dong Hu ◽  
Zhong Wang ◽  
Lijuan Xie ◽  
Yibin Ying
Keyword(s):  
Optical Properties ◽  
Optical Property ◽  
Spatial Frequency ◽  
Frequency Domain ◽  
Measurement Data ◽  
Biological Tissues ◽  
Wide Field ◽  
Food And Agriculture ◽  
Spatial Frequency Domain Imaging ◽  
Spatial Frequency Domain

Measurement of optical properties is critical for understanding light-tissue interaction, properly interpreting measurement data, and gaining better knowledge of tissue physicochemical properties. However, conventional optical measuring techniques are limited in point measurement, which partly hinders the applications on characterizing spatial distribution and inhomogeneity of optical properties of biological tissues. Spatial-frequency domain imaging (SFDI), as an emerging non-contact, depth-varying and wide-field optical imaging technique, is capable of measuring the optical properties in a wide field-of-view on a pixel-by-pixel basis. This review first describes the typical SFDI system and the principle for estimating optical properties using the SFDI technique. Then, the applications of SFDI in the fields of biomedicine, as well as food and agriculture, are reviewed, including burn assessment, skin tissue evaluation, tumor tissue detection, brain tissue monitoring, and quality evaluation of agro-products. Finally, a discussion on the challenges and future perspectives of SFDI for optical property estimation is presented.

scholarly journals Wide‐field optical property mapping and structured light imaging of the esophagus with spatial frequency domain imaging

2019 ◽  
Vol 12 (9) ◽  
Author(s):  
Jordan A. Sweer ◽  
Mason T. Chen ◽  
Kevan J. Salimian ◽  
Richard J. Battafarano ◽  
Nicholas J. Durr
Keyword(s):  
Optical Property ◽  
Spatial Frequency ◽  
Frequency Domain ◽  
Structured Light ◽  
Wide Field ◽  
Spatial Frequency Domain Imaging ◽  
Spatial Frequency Domain

scholarly journals A Pixel-Dependent Finite Element Model for Spatial Frequency Domain Imaging Using NIRFAST

Photonics ◽  
2021 ◽  
Vol 8 (8) ◽  
pp. 310
Author(s):  
Ben O. L. Mellors ◽  
Hamid Dehghani
Keyword(s):  
Optical Property ◽  
Spatial Frequency ◽  
Frequency Domain ◽  
Element Model ◽  
Forward Modeling ◽  
Biological Tissues ◽  
Image Modeling ◽  
Structured Illumination ◽  
Spatial Frequency Domain Imaging ◽  
Spatial Frequency Domain

Spatial frequency domain imaging (SFDI) utilizes the projection of spatially modulated light patterns upon biological tissues to obtain optical property maps for absorption and reduced scattering. Conventionally, both forward modeling and optical property recovery are performed using pixel-independent models, calculated via analytical solutions or Monte-Carlo-based look-up tables, both assuming a homogenous medium. The resulting recovered maps are limited for samples of high heterogeneity, where the homogenous assumption is not valid. NIRFAST, a FEM-based image modeling and reconstruction tool, simulates complex heterogeneous tissue optical interactions for single and multiwavelength systems. Based on the diffusion equation, NIRFAST has been adapted to perform pixel-dependent forward modeling for SFDI. Validation is performed within the spatially resolved domain, along with homogenous structured illumination simulations, with a recovery error of <2%. Heterogeneity is introduced through cylindrical anomalies, varying size, depth and optical property values, with recovery errors of <10%, as observed across a variety of simulations. This work demonstrates the importance of pixel-dependent light interaction modeling for SFDI and its role in quantitative accuracy. Here, a full raw image SFDI modeling tool is presented for heterogeneous samples, providing a mechanism towards a pixel-dependent SFDI image modeling and parameter recovery system.

scholarly journals Halftone spatial frequency domain imaging enables kilohertz high-speed label-free non-contact quantitative mapping of optical properties for strongly turbid media

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Yanyu Zhao ◽  
Bowen Song ◽  
Ming Wang ◽  
Yang Zhao ◽  
Yubo Fan
Keyword(s):  
Optical Properties ◽  
Spatial Frequency ◽  
Frequency Domain ◽  
High Speed ◽  
Turbid Media ◽  
Wide Field ◽  
Label Free ◽  
Spatial Frequency Domain Imaging ◽  
Spatial Frequency Domain

AbstractThe ability to quantify optical properties (i.e., absorption and scattering) of strongly turbid media has major implications on the characterization of biological tissues, fluid fields, and many others. However, there are few methods that can provide wide-field quantification of optical properties, and none is able to perform quantitative optical property imaging with high-speed (e.g., kilohertz) capabilities. Here we develop a new imaging modality termed halftone spatial frequency domain imaging (halftone-SFDI), which is approximately two orders of magnitude faster than the state-of-the-art, and provides kilohertz high-speed, label-free, non-contact, wide-field quantification for the optical properties of strongly turbid media. This method utilizes halftone binary patterned illumination to target the spatial frequency response of turbid media, which is then mapped to optical properties using model-based analysis. We validate the halftone-SFDI on an array of phantoms with a wide range of optical properties as well as in vivo human tissue. We demonstrate with an in vivo rat brain cortex imaging study, and show that halftone-SFDI can longitudinally monitor the absolute concentration as well as spatial distribution of functional chromophores in tissue. We also show that halftone-SFDI can spatially map dual-wavelength optical properties of a highly dynamic flow field at kilohertz speed. Together, these results highlight the potential of halftone-SFDI to enable new capabilities in fundamental research and translational studies including brain science and fluid dynamics.

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