Spatial Frequency Domain Imaging System Research Articles

Deep learning-enabled fluorescence imaging for surgical guidance: in silico training for oral cancer depth quantification.

Oral cancer surgery requires accurate margin delineation to balance complete resection with post-operative functionality. Current in vivo fluorescence imaging systems provide two-dimensional margin assessment yet fail to quantify tumor depth prior to resection. Harnessing structured light in combination with deep learning (DL) may provide near real-time three-dimensional margin detection. A DL-enabled fluorescence spatial frequency domain imaging (SFDI) system trained with in silico tumor models was developed to quantify the depth of oral tumors. A convolutional neural network was designed to produce tumor depth and concentration maps from SFDI images. Three in silico representations of oral cancer lesions were developed to train the DL architecture: cylinders, spherical harmonics, and composite spherical harmonics (CSHs). Each model was validated with in silico SFDI images of patient-derived tongue tumors, and the CSH model was further validated with optical phantoms. The performance of the CSH model was superior when presented with patient-derived tumors ( ). The CSH model could predict depth and concentration within 0.4mm and , respectively, for in silico tumors with depths less than 10mm. A DL-enabled SFDI system trained with in silico CSH demonstrates promise in defining the deep margins of oral tumors.

Using spatial frequency domain imaging to monitor a skin biopsy wound: a pilot study.

Surgical wound infection is a global postoperative issue adding a significant clinical burden and increasing healthcare costs. Early detection and subsequent diagnosis of infection is vital for accurate, early, and effective treatments. In this paper, we report a pilot study exploring spatial frequency domain imaging (SFDI) to monitor, in-vivo, a biopsy wound in human skin. The reduced scattering coefficient, , absorption coefficient, and the oxygen saturation, StO 2, were measured using a SFDI system at 617 and 850 nm. We found the was better capable of monitoring structural changes, possible pus within the wound, re-epithelialization, and collagen fiber remodeling, than with the eye alone. The map is capable of revealing the total hemoglobin distribution in the wound area but was limited in some regions due to the scab covering. This case study indicates SFDI's potential for monitoring and quantifying the process of surgical wound healing and infection.

Ultra-miniature dual-wavelength spatial frequency domain imaging for micro-endoscopy.

There is a need for a cost-effective, quantitative imaging tool that can be deployed endoscopically to better detect early stage gastrointestinal cancers. Spatial frequency domain imaging (SFDI) is a low-cost imaging technique that produces near-real time, quantitative maps of absorption and reduced scattering coefficients, but most implementations are bulky and suitable only for use outside the body. We aim to develop an ultra-miniature SFDI system comprising an optical fiber array (diameter 0.125mm) and a micro camera ( package) to displace conventionally bulky components, in particular, the projector. First, we fabricated a prototype with an outer diameter of 3mm, although the individual component dimensions could permit future packaging to a diameter. We developed a phase-tracking algorithm to rapidly extract images with fringe projections at three equispaced phase shifts to perform SFDI demodulation. To validate the performance, we first demonstrate comparable recovery of quantitative optical properties between our ultra-miniature system and a conventional bench-top SFDI system with an agreement of 15% and 6% for absorption and reduced scattering, respectively. Next, we demonstrate imaging of absorption and reduced scattering of tissue-mimicking phantoms providing enhanced contrast between simulated tissue types (healthy and tumour), done simultaneously at wavelengths of 515 and 660nm. Using a support vector machine classifier, we estimate that sensitivity and specificity values of are feasible for detecting simulated squamous cell carcinoma. This device shows promise as a cost-effective, quantitative imaging tool to detect variations in optical absorption and scattering as indicators of cancer.

Motion-resistant three-wavelength spatial frequency domain imaging system with ambient light suppression using an 8-tap CMOS image sensor.

We present a motion-resistant three-wavelength spatial frequency domain imaging (SFDI) system with ambient light suppression using an 8-tap complementary metal-oxide semiconductor (CMOS) image sensor (CIS) developed at Shizuoka University. The system addresses limitations in conventional SFDI systems, enabling reliable measurements in challenging imaging scenarios that are closer to real-world conditions. Our study demonstrates a three-wavelength SFDI system based on an 8-tap CIS. We demonstrate and evaluate the system's capability of mitigating motion artifacts and ambient light bias through tissue phantom reflectance experiments and in vivo volar forearm experiments. We incorporated the Hilbert transform to reduce the required number of projected patterns per wavelength from three to two per spatial frequency. The 8-tap image sensor has eight charge storage diodes per pixel; therefore, simultaneous image acquisition of eight images based on multi-exposure is possible. Taking advantage of this feature, the sensor simultaneously acquires images for planar illumination, sinusoidal pattern projection at three wavelengths, and ambient light. The ambient light bias is eliminated by subtracting the ambient light image from the others. Motion artifacts are suppressed by reducing the exposure and projection time for each pattern while maintaining sufficient signal levels by repeating the exposure. The system is compared to a conventional SFDI system in tissue phantom experiments and then in vivo measurements of human volar forearms. The 8-tap image sensor-based SFDI system achieved an acquisition rate of 9.4 frame sets per second, with three repeated exposures during each accumulation period. The diffuse reflectance maps of three different tissue phantoms using the conventional SFDI system and the 8-tap image sensor-based SFDI system showed good agreement except for high scattering phantoms. For the in vivo volar forearm measurements, our system successfully measured total hemoglobin concentration, tissue oxygen saturation, and reduced scattering coefficient maps of the subject during motion (16.5cm/s) and under ambient light (28.9lx), exhibiting fewer motion artifacts compared with the conventional SFDI. We demonstrated the potential for motion-resistant three-wavelength SFDI system with ambient light suppression using an 8-tap CIS.

Development of a multispectral spatial-frequency domain imaging system for property and quality assessment of fruits and vegetables

Thanks to the unique features of wide-field, label-free and depth-resolved imaging, spatial-frequency domain imaging (SFDI) technique has witnessed rapid and considerable progress in biomedical, agricultural and food engineering. This paper reports on the design, characterization and calibration of a multipurpose, multispectral SFDI system (550, 600, 630, 675, 710 and 730 nm) for property and quality assessment of fruits and vegetables. The system was mainly composed of illumination unit, imaging unit and sample stage. Customized software was developed to synchronously control pattern generation and shift, light illuminating, image acquisition and saving. Multiple parameters, including field of view, spatial resolution, uniformity, linearity, repeatability and stability, were used to characterize or calibrate the multispectral SFDI system from a systematic view, based on a set of experiments using optical phantoms. The results indicate that the constructed multispectral SFDI system can be used to collect optical property parameters of common fruits and vegetables after calibration. Then the multispectral SFDI system was applied to measure the optical properties of six types of fruits and vegetables (apple, pear, cucumber, tomato, white and green radish), and the measured optical property mappings were utilized for detecting early-stage bruise, which cannot be observed by naked eyes or even conventional uniform lighting imaging. The results demonstrated that the multispectral SFDI system was capable of measuring optical properties, and the reduced scattering coefficient mapping was superior to the absorption coefficient mapping in detecting early-stage bruise. Selection of effective characteristic wavelength could further enhance the bruise detection.

Generic and Model-Based Calibration Method for Spatial Frequency Domain Imaging with Parameterized Frequency and Intensity Correction.

Spatial frequency domain imaging (SFDI) is well established in biology and medicine for non-contact, wide-field imaging of optical properties and 3D topography. Especially for turbid media with displaced, tilted or irregularly shaped surfaces, the reliable quantitative measurement of diffuse reflectance requires efficient calibration and correction methods. In this work, we present the implementation of a generic and hardware independent calibration routine for SFDI setups based on the so-called pinhole camera model for both projection and detection. Using a two-step geometric and intensity calibration, we obtain an imaging model that efficiently and accurately determines 3D topography and diffuse reflectance for subsequently measured samples, taking into account their relative distance and orientation to the camera and projector, as well as the distortions of the optical system. Derived correction procedures for position- and orientation-dependent changes in spatial frequency and intensity allow the determination of the effective scattering coefficient μs' and the absorption coefficient μa when measuring a spherical optical phantom at three different measurement positions and at nine wavelengths with an average error of 5% and 12%, respectively. Model-based calibration allows the characterization of the imaging properties of the entire SFDI system without prior knowledge, enabling the future development of a digital twin for synthetic data generation or more robust evaluation methods.

Application of state equations approach to solve the classical Kubelka-Munk differential equations in turbid environment

The Kubelka-Munk (KM) model is frequently used to describe the optical properties (absorption and scattering) of inhomogeneous media in terms of the measured reflection and transmittance. The classical KM is modeled by two fluxes which counterpropagate in the media and can be described by system of differential equations. This system, on the other hand, can also be rewritten in the form of state equations, widely used in many areas of engineering such as electrical circuits, control systems and more. Here, we describe the simple mathematical expression of light reflectance and transmittance in turbid media based on the KM light propagation model via a system of state equations. To this end, we demonstrate the use of the state equations to solve KM differential equations in a simple and straightforward manner. To validate the solution of our model against the KM solution, different turbid media including tissue phantoms, milk with varying concentrations of sugar, human hands, and mouse brain were tested. We used a spatial frequency domain imaging system to recover the absorption and scattering properties of each of the media. These measured properties were then introduced into both models to obtain diffuse light reflectance and transmittance information. Experimental results demonstrate significant concurrence between the two approaches within a minute difference in all tested cases. The results presented in this study demonstrate the validity of our alternative strategy to the traditional KM solution.

Исследование метрологических характеристик системы визуализации структуры биотканей в пространственно-модулированном излучении

The work is devoted to the study of the measurement accuracy of the spatial frequency domain imaging system for the detection and objective numerical evaluation of optical inhomogeneities in biological tissues. As a result of the initial stage of experimental studies on a stand simulating a spatial frequency domain imaging system, the operating range of spatial frequencies of illuminating irradiation modulation was determined, which ensures maximum reproducibility of the measurement results, and the possibility of achieving a relative measurement error of optical parameters of no more than 10% was shown

Polarization Spatial Frequency Domain Imaging System and Phantom Verification

Polarization Spatial Frequency Domain Imaging System and Phantom Verification

Wavelength and frequency optimization in spatial frequency domain imaging for two-layer tissue

Spatial frequency domain imaging is a non-contact, wide-field, fast-diffusion optical imaging technique, which in principle uses steady-state spatially modulated light to irradiate biological tissue, reconstruct two-dimensional or three-dimensional tissue optical characteristic map through optical transmission model, and further quantify the spatial distribution of tissue physiological parameters by multispectral imaging technique. The selection of light source wavelength and light field spatial modulation frequency is directly related to the accuracy of tissue optical properties and tissue physiological parameters extraction. For improvement of the measurement accuracy of optical properties and physiological parameters in the two-layer tissue, a multispectral spatial frequency domain imaging system is built based on liquid crystal tunable filter, and a data mapping table of spatially resolved diffuse reflectance and optical properties of two-layer tissue is established based on scaling Monte Carlo method. Combined with the dispersion effect and window effect of light-tissue interaction, the study applies numerical simulation to optimize the wavelength in the 650-850 nm range with spectral resolution of 10 nm. In order to minimize the uncertainty of the optical properties, Cramér-Rao bound is used to optimize the optical field spatial modulation frequency by transmitting the uncertainty of optical properties. The results showed that in order to realize the detection of melanin, oxyhemoglobin, deoxyhemoglobin, water and other physiological parameters in two-layer tissue, the best wavelength combination was determined as 720, 730, 760 and 810 nm according to the condition number. The findings of the Cramér-Rao bound analysis reveal that the uncertainty of optical characteristics for the frequency combinations [0, 0.3] mm-1, [0, 0.2] mm-1, and [0, 0.1] mm-1 increases successively. Under the optimal combination of wavelength and frequency, the diffuse reflectance of the gradient gray-scale plate measured by the multi-spectral spatial frequency domain imaging system is linearly correlated with the calibration value. The error between the measured liquid phantom absorption coefficient and the collimation projection system based on colorimetric dish is less than 2%. The experimental results of human brachial artery occlusion indicate that under the optimal wavelength combination, the change of the second layer absorption coefficient captured by the three frequency combinations decreases in turn, so as the change of oxygen saturation.

Optical Property Mapping of Apples and the Relationship With Quality Properties.

This paper reports on the measurement of optical property mapping of apples at the wavelengths of 460, 527, 630, and 710 nm using spatial-frequency domain imaging (SFDI) technique, for assessing the soluble solid content (SSC), firmness, and color parameters. A laboratory-based multispectral SFDI system was developed for acquiring SFDI of 140 “Golden Delicious” apples, from which absorption coefficient (μa) and reduced scattering coefficient (μs′) mappings were quantitatively determined using the three-phase demodulation coupled with curve-fitting method. There was no noticeable spatial variation in the optical property mapping based on the resulting effect of different sizes of the region of interest (ROI) on the average optical properties. Support vector machine (SVM), multiple linear regression (MLR), and partial least square (PLS) models were developed based on μa, μs′ and their combinations (μa × μs′ and μeff) for predicting apple qualities, among which SVM outperformed the best. Better prediction results for quality parameters based on the μa were observed than those based on the μs′, and the combinations further improved the prediction performance, compared to the individual μa or μs′. The best prediction models for SSC and firmness parameters [slope, flesh firmness (FF), and maximum force (Max.F)] were achieved based on the μa × μs′, whereas those for color parameters of b* and C* were based on the μeff, with the correlation coefficients of prediction as 0.66, 0.68, 0.73, 0.79, 0.86, and 0.86, respectively.

Utilizing the spatial frequency domain imaging to investigate change in optical parameters of skin exposed to thermal‐hydrotherapy: Ex‐vivo study

AbstractHydrotherapy is a traditional clinical practice that has been widely used for pain relief. However, immersion in hot water influences skin's moisture and morphology. In this study, we investigate the physiological changes of ex‐vivo chicken skin immersed in hot water (at 40 and 50°C) via monitoring the change in its absorption and scattering properties using the spatial frequency domain imaging (SFDI) technique. The procedure started by calculating the modulation transfer function of the proposed imaging system over a range of spatial frequencies using a high‐resolution test target. Thereafter, structured illumination patterns at different spatial frequencies were projected onto the examined samples via a reflective phase‐only spatial light modulator using transmission and reflection modes. The transmission and reflection images were recorded using a digital camera to reconstruct the optical absorption and scattering parameters. Such parameters were calculated using Kubelka–Munk and lookup table methods. For system validation, the optical properties of two kinds of milk (skimmed and full cream), as reference samples, were reconstructed using the proposed SFDI system in the reflection mode via lookup table method. The results revealed an increase in the scattering coefficient of the skin samples immersed in higher water temperature, while the absorption coefficient values were nearly the same. Furthermore, the obtained results were validated using Monte‐Carlo method showing absolute errors that range from 0.004 to 0.057. In conclusion, the proposed system was presented to investigate the changes in ex‐vivo skin properties under thermal‐hydrotherapy in the context of measured changes in optical parameters.

Quantitative measurement of optical properties and Hb concentration in a rodent model of inflammatory Meibomian gland dysfunction using spatial frequency domain imaging.

Herein, to investigate a new diagnostic method for Meibomian gland dysfunction (MGD) induced by eyelid inflammation, optical properties and deoxy-hemoglobin (Hb) concentrations in rodent eyelid tissues, including Meibomian glands(MGs), were measured using spatial frequency domain imaging (SFDI). Complete Freund's adjuvant solutions were injected into the eyelid margins of Sprague-Dawley rats to induce MGD. After three weeks, the optical properties and Hb of the MG and non-MG regions of the eyelids were measured ex-vivo using an SFDI system. The comparison of Hb showed that the MGD group exhibited significantly higher values than those of the control group in both regions. The optical properties at 730 and 850 nm for the MG regions in the MGD group were significantly different from those in the control group. In addition, the 630 nm absorption coefficients of both regions were significantly higher in the MGD group than in the control group. Thus, the SFDI technique can detect the increased Hb concentration and changes in the optical properties of the eyelids due to inflammatory MGD in a noncontact manner and has the potential to be used as a novel quantitative diagnostic method for the occurrence of MGD.

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.

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

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.

The application of SFDI and LSI system to evaluate the blood perfusion in skin flap mouse model.

The aim of this study is to evaluate whether the blood perfusion to tissues for detecting ischemic necrosis can be quantitatively monitored by spatial frequency domain imaging (SFDI) and laser speckle imaging (LSI) in a skin flap mouse model. Skin flaps were made on Institute of Cancer Research (ICR) mice. Using SFDI and LSI, the following parameters were estimated: oxyhemoglobin (HbO2), deoxyhemoglobin (Hb), total hemoglobin (THb), tissue oxygen saturation (StO2), andspeckle flow index (SFI). Histologically, epithelium thickness, collagen deposition, and blood vessel count of skin flap tissues were analyzed. Then, the correlation of SFDI and histological results was assessed by application of Spearman rank correlation method. As the result, the number of blood vessels and the percentage of collagen areas showed significant difference between the necrotic tissue group and the non-necrotic one. Especially, the necrotic tissue had a complete epithelial loss and loses its normal structure. We identified that SFDI/LSI parameters were significantly different between non-necrotic and necrotic tissue groups. Especially, all SFDI and LSI parameters measured on the 1st day after surgery showed significant difference between necrotic tissue and non-necrotic tissue. In addition, the number of blood vessel and percentage of collagen area were positively correlated with HbO2 and StO2 among SFDI/LSI parameters. Meanwhile, the number of blood vessel and percentage of collagen area showed the negative correlation with Hb. By applying SFDI and LSI simultaneously to the skin flap, we could quantitatively monitor the blood perfusion and the tissue condition which can help us to detect ischemic necrosis objectively in early stage.

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

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.

Spatial frequency domain imaging for determining absorption and scattering properties of bruised pears based on profile corrected diffused reflectance

Curved surface of fruit has a great influence on the measurement of absorption (μa) and reduced scattering coefficients (μ’s) by using the spatial frequency domain imaging (SFDI) technique. In this study, a developed SFDI system was used to conduct phase-measuring profilometry (PMP) to obtain the surface height of tested object. Monte Carlo (MC) simulation was conducted on planar and spherical geometric models, and the correction formula for diffuse reflectance (Rd) was then determined by simulation results and validated by tilt standard reflector. The Rd correction effect on estimating μa and μ’s was revealed by five semi-spherical phantoms, which turned out that both the accuracy and uniformity were substantially improved, with the relative error range of 0.78 %-11.84 % and 2.83 %-8.95 %, and standard deviation range of 1.89 × 10−5 mm-1-1.42 × 10-3 mm-1 and 1.76 × 10-4 mm-1-8.17 × 10-3 mm-1 for corrected μa and μ’s respectively. Finally, the proposed Rd correction method was applied to the bruise detection in pears, the comparisons of μa and μ’s maps between normal and bruised pears were conducted. The results revealed that the area around the highest point of normal pear contour was easily to be identified as bruised area before Rd correction; the μa and μ’s maps for normal pear were more uniform, and for bruised pears after the correction, and the injured area was highlighted for bruised pears. The profile correction method proposed in this study, coupled with the SFDI technique, was essential for precise measurement of μa and μ’s of pear tissues, resulting in less misclassification for bruise detection of pears.

A pilot study on biaxial mechanical, collagen microstructural, and morphological characterizations of a resected human intracranial aneurysm tissue

Intracranial aneurysms (ICAs) are focal dilatations that imply a weakening of the brain artery. Incidental rupture of an ICA is increasingly responsible for significant mortality and morbidity in the American’s aging population. Previous studies have quantified the pressure-volume characteristics, uniaxial mechanical properties, and morphological features of human aneurysms. In this pilot study, for the first time, we comprehensively quantified the mechanical, collagen fiber microstructural, and morphological properties of one resected human posterior inferior cerebellar artery aneurysm. The tissue from the dome of a right posterior inferior cerebral aneurysm was first mechanically characterized using biaxial tension and stress relaxation tests. Then, the load-dependent collagen fiber architecture of the aneurysm tissue was quantified using an in-house polarized spatial frequency domain imaging system. Finally, optical coherence tomography and histological procedures were used to quantify the tissue’s microstructural morphology. Mechanically, the tissue was shown to exhibit hysteresis, a nonlinear stress-strain response, and material anisotropy. Moreover, the unloaded collagen fiber architecture of the tissue was predominantly aligned with the testing Y-direction and rotated towards the X-direction under increasing equibiaxial loading. Furthermore, our histological analysis showed a considerable damage to the morphological integrity of the tissue, including lack of elastin, intimal thickening, and calcium deposition. This new unified characterization framework can be extended to better understand the mechanics-microstructure interrelationship of aneurysm tissues at different time points of the formation or growth. Such specimen-specific information is anticipated to provide valuable insight that may improve our current understanding of aneurysm growth and rupture potential.