Spatial Frequency Domain Imaging Research Articles

Simultaneous Wide-Field Planar Strain-Fiber Orientation Distribution Measurement Using Polarized Spatial Domain Imaging.

In the present study, we demonstrate that soft tissue fiber architectural maps captured using polarized spatial frequency domain imaging (pSFDI) can be utilized as an effective texture source for DIC-based planar surface strain analyses. Experimental planar biaxial mechanical studies were conducted using pericardium as the exemplar tissue, with simultaneous pSFDI measurements taken. From these measurements, the collagen fiber preferred direction [Formula: see text] was determined at the pixel level over the entire strain range using established methods ( https://doi.org/10.1007/s10439-019-02233-0 ). We then utilized these pixel-level [Formula: see text] maps as a texture source to quantify the deformation gradient tensor [Formula: see text] as a function of spatial position [Formula: see text] within the specimen at time t. Results indicted that that the pSFDI approach produced accurate deformation maps, as validated using both physical markers and conventional particle based method derived from the DIC analysis of the same specimens. We then extended the pSFDI technique to extract the fiber orientation distribution [Formula: see text] as a function of [Formula: see text] from the pSFDI intensity signal. This was accomplished by developing a calibration procedure to account for the optical behavior of the constituent fibers for the soft tissue being studied. We then demonstrated that the extracted [Formula: see text] was accurately computed in both the referential (i.e. unloaded) and deformed states. Moreover, we noted that the measured [Formula: see text] agreed well with affine kinematic deformation predictions. We also demonstrated this calibration approach could also be effectively used on electrospun biomaterials, underscoring the general utility of the approach. In a final step, using the ability to simultaneously quantify [Formula: see text] and [Formula: see text], we examined the effect of deformation and collagen structural measurements on the measurement region size. For pericardial tissues, we determined a critical length of [Formula: see text] 8 mm wherein the regional variations sufficiently dissipated. This result has immediate potential in the identification of optimal length scales for meso-scale strain measurement in soft tissues and fibrous biomaterials.

Spatial frequency domain imaging technology based on Fourier single-pixel imaging

.SignificanceOptical properties (absorption coefficient and scattering coefficient) of tissue are the most critical parameters for disease diagnosis-based optical method. In recent years, researchers proposed spatial frequency domain imaging (SFDI) to quantitatively map tissue optical properties in a broad field of contactless imaging. To solve the limitations in wavebands unsuitable for silicon-based sensor technology, a compressed sensing (CS) algorithm is used to reproduce the original signal by a single-pixel detectors. Currently, the existing single-pixel SFDI method mainly uses a random sampling policy to extract and recover signals in the acquisition stage. However, these methods are memory-hungry and time-consuming, and they cannot generate discernible results under low sampling rate. Explorations on high performance and efficiency single-pixel SFDI are of great significance for clinical application.AimFourier single-pixel imaging can reconstruct signals with less time and space costs and has fewer reconstruction errors. We focus on an SFDI algorithm based on Fourier single-pixel imaging and propose our Fourier single-pixel image-based spatial frequency domain imaging method (FSI-SFDI).ApproachFirst, we use Fourier single-pixel imaging algorithm to collect and compress signals and SFDI algorithm to generate optical parameters. Given the basis that the main energy of general image signals is concentrated in the range of low frequency of Fourier frequency domain, our FSI-SFDI uses a circular-sampling scheme to sample data points in the low-frequency region. Then, we reconstruct the image details from these points by optimization-based inverse-FFT method.ResultsOur algorithm is tested on simulated data. Results show that the root mean square error (RMSE) of optical parameters is lower than 5% when the data reduction is 92%, and it can generate discernible optical parameter image with low sampling rate. We can observe that our FSI-SFDI primarily recovers the optical properties while keeping the RMSE under the upper bound of 4.5% when we use an image with resolution as the example for calculation and analysis. Not only that but also our algorithm consumes less space and time for an image with resolution, the signal reconstruction takes only 1.65 ms, and requires less RAM memory. Compared to CS-SFDI method, our FSI-SFDI can reduce the required number of measurements through optimizing algorithm.ConclusionsMoreover, FSI-SFDI is capable of recovering high-quality resolvable images with lower sampling rate, higher-resolution images with less memory and time consumed than previous CS-SFDI method, which is very promising for clinical data collection and medical analysis.

An Approach for Extracting Optical and Physiological Parameters of Human Skin Tissue Based on Spatial Frequency Domain Imaging

An Approach for Extracting Optical and Physiological Parameters of Human Skin Tissue Based on Spatial Frequency Domain Imaging

Noninvasive Quantitative Assessment of Burn Degree Based on Spatial Frequency-Domain Imaging

Noninvasive Quantitative Assessment of Burn Degree Based on Spatial Frequency-Domain Imaging

Single-Fiber Diffuse Reflectance Spectroscopy and Spatial Frequency Domain Imaging in Surgery Guidance: A Study on Optical Phantoms.

Diffuse reflectance spectroscopy (DRS) and imaging are increasingly being used in surgical guidance for tumor margin detection during endoscopic operations. However, the accuracy of the boundary detection with optical techniques may depend on the acquisition parameters, and its evaluation is in high demand. In this work, using optical phantoms with homogeneous and heterogeneous distribution of chromophores mimicking normal and pathological bladder tissues, the accuracy of tumor margin detection using single-fiber diffuse reflectance spectroscopy and spatial frequency domain imaging was evaluated. We also showed how the diffuse reflectance response obtained at different spatial frequencies with the spatial frequency domain imaging technique could be used not only to quantitatively map absorption and scattering coefficients of normal tissues and tumor-like heterogeneities but also to estimate the tumor depth localization. The demonstrated results could be helpful for proper analysis of the DRS data measured in vivo and for translation of optical techniques for tumor margin detection to clinics.

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

The 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.

Assessing soluble solid content and texture of pear during shelf-life period by single snapshot spatial frequency domain imaging

Spatial frequency domain imaging (SFDI) is a promising technique for its merits of noncontact and wide-field detection. However, considering the cost and detection speed, it has not been put into widespread application in agro-products. In this study, the low-cost, fast SFDI system and matching software were adopted to realize determination of absorption ( μ a ) and reduced scattering coefficients ( μ′ s ) of pears. The spatial frequencies ( f x ) were calibrated and system linearity was verified, the results showed that excellent linearity was obtained. Single snapshot demodulation was adopted, the validation results conducted on 390 liquid phantoms indicated that the optimal f x for snapshot method is 1/3 mm −1 . Fast calculation models for μ a and μ′ s developed by least squares support vector regression (LSSVR) based on Monte Carlo (MC) simulations were then applied and validated at six wavelengths (460, 503, 527, 630, 658 and 675 nm). The results demonstrated that the LSSVR models could realize precise calculation for μ a or μ′ s . Finally, the variation trends of μ a , μ′ s , soluble solids content (SSC) and texture (MT firmness, flesh firmness, stiffness, brittleness and adhesiveness) of 9 batches of pears were analysed, and prediction models were developed by artificial neural network (ANN) based on μ a and μ′ s respectively. The results showed that for texture estimation, the prediction effect was relative well by using μ′ s , especially for brittleness and adhesiveness, while the accuracy for SSC was limited by only six μ a features. Future research should focus on the acquisition of more spectral information to improve model accuracy. • Calibrated SFDI system and validated linearity for modulated light. • Validated single snapshot method and LSSVR models for μ a , μ′ s at six wavelengths. • Analysed the variations of μ a , μ′ s SSC and texture parameters of pear in shelf-life. • Built ANN models for SSC and texture of pear based on μ a , μ′ s respectively.

Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures

High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e−11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e−14). Extending the radiomics approach to high-dimensional optical data—termed “optomics” in this study—offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available.

Linking collagen fiber architecture to tissue-level biaxial mechanical behaviors of porcine semilunar heart valve cusps

The semilunar heart valves regulate the blood flow from the ventricles to the major arteries through the opening and closing of the scallop shaped cusps. These cusps are composed of collagen fibers that act as the primary loading-bearing component. The load-dependent collagen fiber architecture has been previously examined in the existing literature; however, these studies relied on chemical clearing and tissue modifications to observe the underlying changes in response to mechanical loads. In the present study, we address this gap in knowledge by quantifying the collagen fiber orientations and alignments of the aortic and pulmonary cusps through a multi-scale, non-destructive experimental approach. This opto-mechanical approach, which combines polarized spatial frequency domain imaging and biaxial mechanical testing, provides a greater field of view (10–25mm) and faster imaging time (45–50s) than other traditional collagen imaging techniques. The birefringent response of the collagen fibers was fit with a von Mises distribution, while the biaxial mechanical testing data was implemented into a modified full structural model for further analysis. Our results showed that the semilunar heart valve cusps are more extensible in the tissue’s radial direction than the circumferential direction under all the varied biaxial testing protocols, together with greater material anisotropy among the pulmonary valve cusps compared to the aortic valve cusps. The collagen fibers were shown to reorient towards the direction of the greatest applied loading and incrementally realign with the increased applied stress. The collagen fiber architecture within the aortic valve cusps were found to be more homogeneous than the pulmonary valve counterparts, reflecting the differences in the physiological environments experienced by these two semilunar heart valves. Further, the von Mises distribution fitting highlighted the presence and contribution of two distinct fiber families for each of the two semilunar heart valves. The results from this work would provide valuable insight into connecting tissue-level mechanics to the underlying collagen fiber architecture—an essential information for the future development of high-fidelity aortic/pulmonary valve computational models.

Measurement of absorption and scattering properties of milk using a hyperspectral spatial frequency domain imaging system

Measurement of absorption and scattering properties of milk using a hyperspectral spatial frequency domain imaging system

Multimodal hyperspectral fluorescence and spatial frequency domain imaging for tissue health diagnostics of the oral cavity.

A multimodal, hyperspectral imaging system was built for diagnostics of oral tissues. The system, termed Hyperspectral-Fluorescence-Spatial Frequency Domain Imaging (Hy-F-SFDI), combines the principles of spatial frequency domain imaging, quantitative light fluorescence, and CIELAB color measurement. Hy-F-SFDI employs a compact LED projector, excitation LED, and a 16 channel hyperspectral camera mounted on a custom platform for tissue imaging. A two layer Monte Carlo approach was used to generate a reference table for quick tissue analysis. To demonstrate the clinical capabilities of Hy-F-SFDI, we used the system to quantify gingival tissue hemoglobin volume fraction, detect caries, bacterial activity, and measure tooth color of a volunteer at different time points. Hy-F-SFDI was able to measure quantitative changes in tissue parameters.

A Quantitative Assessment of Wound Healing With Oxygenated Micro/Nanobubbles in a Preclinical Burn Model.

Burns are devastating injuries, carry significant morbidity, and require long-term treatment or multiple reconstructive procedures. Wound healing and secondary insults caused by burn wound conversion are amendable to therapeutic intervention, where ischemia has been cited as one of the major factors (Dermatol Surg. 2008;34:1159-1169). Halting injury progression in the zone of stasis is crucial as conversion creates increased burn surface area and depth, leading to local and systemic consequences (J Burns Wounds. 2006;5:e2). Oxygen-carrying micro/nanobubbles, MNB(O2), offer a novel technology that can be used to effectively deliver oxygen to burn wounds and potentially counteract burn wound ischemia. Topical irrigation with MNB(O2) of full-thickness burn wounds on a rodent model (n = 3) was compared against saline-treated controls (n = 3). Tissue structure (reduced scattering coefficient, μs'), oxyhemoglobin concentration (cHbO2), and tissue perfusion were quantified over the course of 28 days through spatial frequency domain imaging and laser speckle imaging. Histological samples taken at the end of the experiment were examined for evidence of wound healing. Findings in this preliminary study showed hastened healing with significant differences in spatial frequency domain imaging-measured μs' during wound healing (days 11-28) in MNB(O2) group. The healing "tipping point" seemed to occur at days 9 to 11 with increased collagen organization and increased cHbO2 occurring around that period confirming the gross healing improvements observed. In addition, histological evidence indicated that only the MNB(O2) burns had reached the remodeling phase by the end of 28-day study period. These preliminary findings propose the potential of MNB(O2) as a topical method for improving burn wound healing.

Imaging sub-diffuse optical properties of cancerous and normal skin tissue using machine learning-aided spatial frequency domain imaging.

.Significance: Sub-diffuse optical properties may serve as useful cancer biomarkers, and wide-field heatmaps of these properties could aid physicians in identifying cancerous tissue. Sub-diffuse spatial frequency domain imaging (sd-SFDI) can reveal such wide-field maps, but the current time cost of experimentally validated methods for rendering these heatmaps precludes this technology from potential real-time applications.Aim: Our study renders heatmaps of sub-diffuse optical properties from experimental sd-SFDI images in real time and reports these properties for cancerous and normal skin tissue subtypes.Approach: A phase function sampling method was used to simulate sd-SFDI spectra over a wide range of optical properties. A machine learning model trained on these simulations and tested on tissue phantoms was used to render sub-diffuse optical property heatmaps from sd-SFDI images of cancerous and normal skin tissue.Results: The model accurately rendered heatmaps from experimental sd-SFDI images in real time. In addition, heatmaps of a small number of tissue samples are presented to inform hypotheses on sub-diffuse optical property differences across skin tissue subtypes.Conclusion: These results bring the overall process of sd-SFDI a fundamental step closer to real-time speeds and set a foundation for future real-time medical applications of sd-SFDI such as image guided surgery.

Spatial Frequency Domain Imaging System Calibration, Correction and Application for Pear Surface Damage Detection.

Spatial frequency domain imaging (SFDI) is a non-contact wide-field optical imaging technique for optical property detection. This study aimed to establish an SFDI system and investigate the effects of system calibration, error analysis and correction on the measurement of optical properties. Optical parameter characteristic measurements of normal pears with three different damage types were performed using the calibrated system. The obtained absorption coefficient μa and the reduced scattering coefficient μ’s were used for discriminating pears with different surface damage using a linear discriminant analysis model. The results showed that at 527 nm and 675 nm, the pears’ quadruple classification (normal, bruised, scratched and abraded) accuracy using the SFDI technique was 92.5% and 83.8%, respectively, which has an advantage compared with the conventional planar light classification results of 82.5% and 77.5%. The three-way classification (normal, minor damage and serious damage) SFDI technique was as high as 100% and 98.8% at 527 nm and 675 nm, respectively, while the classification accuracy of conventional planar light was 93.8% and 93.8%, respectively. The results of this study indicated that SFDI has the potential to detect different damage types in fruit and that the SFDI technique has a promising future in agricultural product quality inspection in further research.

In vivo two-dimensional quantitative imaging of skin and cutaneous microcirculation with perturbative spatial frequency domain imaging (p-SFDI).

We introduce perturbative spatial frequency domain imaging (p-SFDI) for fast two-dimensional (2D) mapping of the optical properties and physiological characteristics of skin and cutaneous microcirculation using spatially modulated visible light. Compared to the traditional methods for recovering 2D maps through a pixel-by-pixel inversion, p-SFDI significantly shortens parameter retrieval time, largely avoids the random fitting errors caused by measurement noise, and enhances the image reconstruction quality. The efficacy of p-SFDI is demonstrated by in vivo imaging forearm of one healthy subject, recovering the 2D spatial distribution of cutaneous hemoglobin concentration, oxygen saturation, scattering properties, the melanin content, and the epidermal thickness over a large field of view. Furthermore, the temporal and spatial variations in physiological parameters under the forearm reactive hyperemia protocol are revealed, showing its applications in monitoring temporal and spatial dynamics.

Assessing multimodal optical imaging of perfusion in burn wounds

A critical need exists for early, accurate diagnosis of burn wound severity to help identify the course of treatment and outcome of the wound. Laser speckle imaging (LSI) is a promising blood perfusion imaging approach, but it does not account for changes in tissue optical properties that can occur with burn wounds, which are highly dynamic environments. Here, we studied optical property dynamics following burn injury and debridement and the associated impact on interpretation of LSI measurements of skin perfusion. We used spatial frequency domain imaging (SFDI) measurements of tissue optical properties to study the impact of burn-induced changes in these properties on LSI measurements. An established preclinical porcine model of burn injury was used (n = 8). SFDI and LSI data were collected from burn wounds of varying severity. SFDI measurements demonstrate that optical properties change in response to burn injury in a porcine model. We then apply theoretical modeling to demonstrate that the measured range of optical property changes can affect the interpretation of LSI measurements of blood flow, but this effect is minimal for most of the measured data. Collectively, our results indicate that, even with a dynamic burn wound environment, blood-flow measurements with LSI can serve as an appropriate strategy for accurate assessment of burn severity.

Simple demodulation method for optical property extraction in spatial frequency domain imaging.

Different demodulation methods affect the efficiency and accuracy of spatial frequency domain imaging (SFDI). A simple and effective method of sum-to-product identities (STPI) demodulation was proposed in this study. STPI requires one fewer image than conventional three-phase demodulation (TPD) at a spatial frequency. Numerical simulation and phantom experiments were performed. The result proved the feasibility of STPI and showed that STPI combined with subtraction can achieve high-precision demodulation in the low spatial frequency domain. Through extraction of phantom optical properties, STPI had similar accuracy compared with other demodulation methods in extracting optical properties in phantoms. STPI was also used to extract the optical properties of milk, and it had highly consistent results with TPD, which can distinguish milk with different fat content. The demodulation effect of this method in the low spatial frequencies is better than other fast demodulation methods.

Spatial frequency domain imager based on a compact multiaperture camera: testing and feasibility for noninvasive burn severity assessment.

.Significance: Spatial frequency domain imaging (SFDI) is a wide-field imaging technique that provides quantitative maps of tissue optical properties. We describe a compact SFDI imager that employs a multispectral compound-eye camera. This design enables simultaneous image acquisition at multiple wavelengths. Such a device has potential for application for quantitative evaluation of superficial tissues by nonspecialists in low-resource settings.Aim: The aim of this work was to develop a compact SFDI imager for widefield imaging of in-vivo tissue optical properties and verify its ability to measure optical properties of tissue-simulating phantoms and in a preclinical model of burn wounds.Approach: This compound-eye imager was constructed using a CMOS sensor subdivided into multiple regions, each having a bandpass filter and objective lens. The ability of the instrument to image optical properties was compared with (1) a commercial SFDI imager and (2) a laboratory-based system. Initial validation of ability to accurately characterize optical properties was performed using a tissue-simulating optical phantom. It was then applied to an established murine model of thermal contact burn severity. In-vivo measurements of the optical properties of rat skin were performed before and after the application of burns. Histology was used to verify burn severity.Results: Measurements of the tissue-simulating phantom optical properties made using the compound-eye imager agree with measurements made using the two comparison SFDI devices. For the murine burn model, the burns showed a decrease in the reduced scattering coefficient at all measurement wavelengths compared with preburn measurements at the same locations. This is consistent with previously reported changes in scattering that occur in full-thickness burns.Conclusion: We demonstrate the potential for SFDI to be translated into compact form factor using a compound-eye camera that is capable of obtaining multiple wavelengths channels simultaneously.

Determining the optical properties of apple tissue and their dependence on physiological and morphological characteristics during fruit maturation. Part 2: Mie's theory

Mie's theory was used to develop a theoretical model to describe light propagation in apple tissue based on its microstructural properties. Taking into account the size distributions and volume fractions of intercellular space and starch granules, which are known in detail from previous studies, the model predicted a decrease in the effective scattering coefficient μ′s of about 30 % during maturation. For the lateral change of μ′s within a ripe apple, the model predicted an increase up to 35 % from core to skin. In both cases, the relative changes agree well with the experimental results obtained with spatial frequency domain imaging (SFDI) and an integrating sphere setup. Based on the model, at least 70 % of total μ′s is attributable to intercellular space, which accordingly plays a dominant role in the temporal and lateral change of scattering. Using an extended Mie model for layered particles assuming a dense cell structure, a negligible effect on μ′s was observed for the cell wall. However, for cells separated from the surrounding tissue by a narrow air gap (e.g. dissolution of the middle lamella), μ′s was 20 % higher than for cells theoretically isolated in air. Lastly, it was shown that an increase in soluble solids content (SSC) during maturation by up to 15 % and the associated higher refractive index in the cells led to an increase in μ′s by about 3–5 % compared to the case without considering SSC. Overall, the application of Mie's theory proved suitable to investigate the influence of different morphological structures on light scattering in apple tissue.

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

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.