Biomedical Optics Express

Three-photon microscopy enables deep-tissue imaging but is highly sensitive to excitation pulse quality, since three-photon excitation efficiency scales with the cube of instantaneous intensity. Group-delay dispersion (GDD) and third-order dispersion (TOD) accumulated through the laser and microscope optics can substantially reduce peak intensity at the focal plane, yet these quantities are rarely measured where imaging occurs. Here, we use third-harmonic generation (THG) interferometric autocorrelation, together with Dispersion Look-Up-Table Estimation (D-LUTE) and a joint two-measurement fitting procedure validated on synthetic data, to estimate baseline GDD and TOD directly at the objective focal plane, requiring only a compact autocorrelator module added to the microscope beam path. Applying this method at 1300 nm and 1600 nm excitation across two microscope systems equipped with different units of the same laser model, we find pulse durations 1.4- to 1.7-fold longer than the transform limit at every condition, driven predominantly by TOD, which varied by roughly 2.7-fold between the two systems. Using the endogenous THG signal from myelinated fibers, we further demonstrate in vivo pulse characterization in the mouse brain, finding no measurable broadening between the tissue surface and a depth of nearly a millimeter. This low-cost, easily implemented approach enables routine, in situ pulse monitoring across multiphoton microscopy platforms.

Coherent structured illumination microscopy (c-SIM) is a synthetic aperture optical technique for sub-diffraction limit imaging that extends the utility of traditional SIM to non-fluorescent samples. Here, we present a complementary 5-beam implementation of c-SIM that provides enhanced optical sectioning compared to conventional quadrupolar illumination. Since our approach detects intensity images due to coherent light scattering, it avoids the complications associated with detecting complex fields. Through comparative measurements on calibration samples and live microalgae, we show that 5-beam c-SIM effectively suppresses coherent defocus effects, improving image quality while simultaneously providing a 2-fold lateral resolution improvement.

Significance: Continuous, noninvasive, and depth-resolved monitoring of blood-flow-related tissue dynamics remains an important unmet need. Speckle-contrast optical spectroscopy (SCOS), including interferometric implementations such as iSCOS, provides a scalable optical route to blood-flow sensing, but conventional continuous-wave approaches lack intrinsic depth selectivity. Time-of-flight (TOF) gating offers a way to separate superficial and deeper dynamic contributions in layered tissues, such as skin-muscle or scalp-cortex, by resolving photon path lengths. Aim: We introduce a swept-source, single-channel implementation of interferometric speckle-contrast optical spectroscopy (iSCOS) to obtain TOF-resolved temporal speckle contrast, {kappa}^2, from the measured field autocorrelation g_1, and evaluate its feasibility for depth-resolved blood-flow sensing. Approach: A swept-source iNIRS system operating at 780 nm acquired interferometric signals, which were Fourier-transformed along the optical-frequency axis to recover complex TOF-resolved speckle fields. Temporal speckle contrast was then estimated at each TOF gate indirectly from g_1 using the speckle-visibility relation. Diffusion-based numerical simulations were first used to compare the direct variance-based estimator and the indirect g_1-based estimator under varying reduced scattering coefficient, diffusion coefficient, additive noise level, and bi-layer geometry. Because the simulations showed that the g_1-derived {kappa}^2 estimator was substantially less sensitive to additive noise than the direct estimator, this estimator was used for the main phantom and in vivo analyses, while the direct estimator served as a simulation comparator. The g_1-derived estimator was then applied to liquid and bi-layer phantoms, followed by proof-of-concept in vivo measurements on the human forearm during cuff occlusion and on the forehead during a Sudoku task. Results: TOF-resolved kappa2 curves recovered with the g_1-derived estimator matched DWS theory across scattering coefficients, photon path lengths, and exposure times. The estimator preserved theoretical accuracy for additive noise amplitudes up to 50% of the field amplitude, whereas the direct variance estimator showed substantial noise-induced bias and required correction. Bi-layer simulations and phantom experiments reproduced the predicted direction and onset of TOF-dependent decorrelation-rate trends in layered media. In vivo, the recovered blood-flow index tracked the expected TOF-dependent cuff-occlusion and reactive-hyperemia response in the forearm. During the single-subject Sudoku task, the left-forehead recording showed a TOF-dependent relative blood-flow-index increase of +0.8 {+/-} 1.9% at TOF = 400 ps, +9.8 {+/-} 2.2% at TOF = 600 ps, and +15.2 {+/-} 5.6% at TOF = 800 ps. This pattern is consistent with increased sensitivity to deeper tissue at longer photon path lengths, but requires cohort-level validation before quantitative interpretation as cognitive activation. Conclusions: Coupling temporal speckle-contrast analysis with swept-source iNIRS yields a proof-of-concept, depth-resolved platform for blood-flow sensing. By estimating TOF-resolved speckle contrast through the g_1-derived {kappa}^2 route, TOF-iSCOS suppresses additive-noise bias while preserving sensitivity to deeper dynamic tissue layers. The present single-channel results bridge continuous-wave iSCOS, interferometric NIRS and time-domain diffuse correlation spectroscopy (TD-DCS), and motivate future multi-channel and cohort studies for scalable cortical hemodynamic monitoring.

While light-sheet microscopy is emerging as a robust method for volumetric imaging with improved axial resolution, its capability regarding two-dimensional, surface-level mapping is often hindered by limitations in data redundancy and reconstruction efficiency stemming from volumetric registration methods. We demonstrate that a multiview imaging approach in an axially-swept, dithered light-sheet microscope paired with computational image reconstruction of view projections is able to address these trade-offs to enable large-scale mapping of surface structural features, leveraging the advantages of multiview light-sheet in scalable field of view, working distance, and near isotropic resolution across the entire imaging depth. To aid in the acquisition and analysis of two-dimensional surface structures, we present a tailored surface mapping workflow and a Fiji plugin for computational reconstruction, promoting robust and comprehensive visualization of surface features of uncleared volumetric samples. Our strategy, termed projection reconstruction for imaging surface morphology (PRISM), integrates axially swept dithered light-sheet microscopy and post-processing software for multiview imaging. The imaging hardware enables near-isotropic resolution across its entire field of view, while the software implementation leverages rigid and affine transformations to align two-dimensional projections of multiview samples. It is designed to work with the BigStitcher pipeline, leveraging its robust algorithm to provide support for two-dimensional image alignment and stitching. We demonstrate the capability of PRISM in studies of lymphatic network mapping in the epicardial layer of intact mouse hearts, as well as surface profiles of FaDu spheroids labeled with antibody-nanodiamond conjugates. This method allows us to quantify cardiac lymphatic branch numbers, diameters, and lengths of a Prox1-tdTomato mouse cardiac model, as well as cluster number and diameters of epidermal growth factor receptor within a FaDu spheroid labeled with a nanodiamond-antibody conjugate, with a significant reduction of post-processing data size. PRISM leverages multiview image projections to promote studies of cardiac lymphatics in mouse models and surface receptor distributions within spheroid models, enabling efficient surface mapping of large, intact, and uncleared biological samples across a variety of scales.

Bone adapts to its mechanical and physiological environment through the coordinated actions of osteocytes and marrow-resident cell populations. Because these processes depend on complex interactions within native tissue microenvironments, intravital imaging offers a unique opportunity to reveal cellular behaviors that cannot be fully captured ex vivo. However, the highly scattering nature of mineralized bone limits imaging depth and direct observation of cells within intact tissue. Two-photon (2P) microscopy has enabled important advances in bone biology, while three-photon (3P) microscopy has been proven to extend imaging depth and image quality in skeletal tissues. Here, we directly compared the performance of 2P and 3P microscopy in ex vivo mouse long bones by quantifying laser attenuation, signal-to-noise ratio, signal-to-background ratio, and spatial resolution, as well as assessed the impact of wave-front correction. We found that 2P and 3P microscopy generated comparable image quality through approximately 50 {micro}m of cortical bone. Beyond this depth, however, 3P microscopy provided superior brightness, contrast, and resolution, enabling improved visualization of structures deep within the cortex and at the cortical-marrow interface. To assess compatibility with intravital imaging, we evaluated endogenous markers of cellular stress during 3P imaging. Although prolonged continuous imaging decreased osteocyte spontaneous calcium signaling magnitude and increased autofluorescence, short intermittent imaging bouts produced negligible evidence of cellular damage compared to controls. Leveraging the enhanced penetration depth of 3P microscopy, we further show visualization of immune cell migration within the marrow cavity through intact cortical bone in both the third metatarsal (MT3) and tibia. Together, these findings affirm 3P microscopy as a powerful tool for studying cellular dynamics in living bone. By extending imaging beyond superficial cortical regions and enabling direct visualization of marrow-resident cells through intact bone, 3P microscopy expands opportunities to investigate osteocyte biology, marrow niche function, and skeletal adaptation in vivo.

Motion artifacts present a major challenge for intravital imaging of tissues undergoing physiological movement or mechanical loading. Blurring or artificial changes in image intensity due to shifting on the z-axis reduce data reproducibility and reliability. Existing post-acquisition approaches can partially compensate for motion, but they increase experimental complexity and are not well suited for use in mechanically loaded bone. Therefore, we developed a novel method for real-time correction of axial motion during mechanical loading of bone by synchronizing the movement of the objective to the actuator. Synchronization was achieved by linking the position of the actuator piezo motor to the objective piezo motor with a user refined reduction via potentiometer. Applying axial motion correction effectively removed artificial changes in fluorescent intensity in a static fluorescent marker up to 3000{varepsilon} in bone as measured by similarity and average intensity before and during loading. This improvement was reflected in the improved accuracy in capture of a dynamic fluorescent calcium indicator (GCaMP6f) in osteocytes. Our system provides a user-friendly, robust framework that can be easily adapted to other mechanically loaded tissues, improving data collection and expanding the utility of two-photon imaging across a variety of biological applications.

Optical recording from large numbers of neurons is an indispensable technique for studying neuronal ensembles. We use optical sectioning through pinhole illumination to reduce the background fluorescence (F0) and increase the optical signal ({Delta}F/F0) in ex vivo brain slices densely labeled with GCaMP6f, allowing an ordinary fluorescence microscope to capture calcium transients from over 300 individual CA1 neurons - a marked increase compared to ordinary wide field fluorescence illumination. Multiple layers of overlapping neurons can be identified by their locations and the shape in space of their {Delta}F/F0 images. A single pinhole mask was placed at the field stop of a wide field illuminator, and the image of the pinhole was projected onto the tissue by a 20X NA 0.95 water immersion objective (Olympus). This created an illuminated disk with a diameter of [~]200 m and optical sections of hippocampal CA1 pyramidal layer tissue [~]100 m thick. This illumination blocked a large fraction of the F0, which in turn increased the {Delta}F/F0 5-10-fold compared to that of wide field illumination. When putative pyramidal neurons fire sparsely in the brain slice, up to 300 partially superimposed neurons can be identified by their shape and spatial location in the thick ([~]480 m) ex vivo slice in the CA1 area surrounding the pinhole image. The signal-to-noise ratio was adequate even at a low excitation light level of [~]20k photoelectrons per pixel well on the camera, allowing for 3,000 seconds of total recording time without significant bleaching. This pinhole "half confocal" method has created a useful way to sample calcium transient signals in thick tissue with a large population of neurons densely labeled with GCaMP-6f.

Spectroscopic single-molecule localization microscopy (sSMLM) enables multiplexed super-resolution imaging by simultaneously acquiring the spatial position and spectral information of individual fluorophores. Dual-wedge prism (DWP)-based implementations provide a compact, alignment-stable approach to spectral dispersion, but trade-offs between localization precision, spectral precision, and experimental complexity remain. We systematically compare five DWP-based sSMLM configurations, including two-dimensional (2D) and three-dimensional (3D) implementations using single DWP (DWP-sSMLM) and symmetrically-dispersed DWP (SDDWP-sSMLM). We evaluate lateral precision, spectral precision, and ease of use. SDDWP configurations acquire spectral images in both channels and utilize both for spatial localization, yielding the highest lateral and spectral precision. However, for applications that do not require axial information, 2D-DWP provides a simple, plug-and-play solution with robust performance. This work offers a guideline for selecting DWP configurations based on experimental needs.

Light-sheet fluorescence microscopy (LSFM) has revolutionized biological imaging by enabling high spatial and temporal resolution with minimal photodamage. However, conventional LSFM techniques often suffer from striping artifacts in the resulting images due to light scattering and absorption within samples, leading to uneven illumination that negatively impacts the accuracy of subsequent image analyses. To address this limitation, we introduce dodecagon light-sheet fluorescence microscopy (dodecaLSFM), a novel approach that maximizes angular diversity to achieve homogeneous illumination and suppress striping artifacts. dodecaLSFM employs diffraction optics and cylindrical lenses to generate twelve light sheets, providing 360 degree omnidirectional illumination that significantly enhances illumination uniformity compared to traditional mSPIM, mDSLM, and ultramicroscopy systems, which use only one or two illumination planes. We demonstrate the effectiveness of dodecaLSFM by achieving high-resolution imaging of whole mouse brain vasculature following tissue clearing, allowing precise morphometric analysis of vascular networks without striping artifacts. Furthermore, we show that combining dodecaLSFM with expansion microscopy (ExM) enables whole-organ 3D imaging at cellular resolution. This novel approach provides an advanced, scalable solution for large-volume imaging, facilitating detailed structural and functional studies across diverse biological applications.

Alterations of fluorescence properties in retinal pigment epithelium (RPE) cells caused by diseases such as age-related macular degeneration (AMD) highlight the need for detailed analysis of the fluorescent RPE granules at the individual level. Precise segmentation and classification of these granules remain challenging due to their limited visual separability. In this study, we present Classi4RPE, a computational algorithm designed to accurately segment RPE granules and classify them into three categories -- lipofuscin (L), melanolipofuscin (ML), and melanin (M) -- based on fluorescence lifetime imaging data, which provide distinctive contrast. The method is implemented in a custom Python framework and employs seeded watershed segmentation to isolate individual granules. Lipofuscin granules are identified as hyperfluorescent structures with longer lifetimes, while granules with shorter lifetimes are further analyzed based on their spatial lifetime distribution from the center to edge, enabling discrimination of ML from other melanin-rich granules. Our approach achieves high performance, with mean sensitivities of 0.99 for L granules and 0.90 for ML granules, and corresponding specificities of 0.93 and 0.98, respectively, compared to manually annotated ground truth. These results demonstrate the potential of Classi4RPE to surpass human visual limitations and provide a robust tool for quantitative RPE analysis.

Minimally invasive surgery is a powerful technique that enables operations deep within the body while minimizing patient trauma and recovery time. Optical endoscopes are key to providing intraoperative vision but still face challenges due to the loss of essential senses, including depth perception and tactile feedback for tissue evaluation. Thus, it is critical to develop endoscopic imaging technologies that can augment operators with critical information. In this work, we explore a prototype multimodal 3D imaging endoscope that integrates volumetric light-field imaging with laser-speckle contrast imaging to simultaneously capture 3D structure and blood-flow information in a clinically relevant form factor.

Intracellular dynamics span a broad range of time scales and biomolecular processes, offering insights into cell health, functional state, phenotype, and response to external perturbations. Several label-free optical imaging approaches have been used to capture intracellular dynamics but are limited by spatiotemporal resolution and biomolecular specificity required to distinguish unique subcellular and metabolic processes. In this work, we demonstrate deep-ultraviolet (UV) microscopy as a powerful, label-free, high-resolution approach for quantifying multiscale intracellular dynamics with biomolecular specificity. By leveraging power spectral analysis and phasor analysis, we capture multiscale intracellular dynamics and analyze their UV wavelength-dependent behavior predicated by the absorption of different endogenous biomolecules. We apply this technique to prostate epithelial cell lines of increasing malignancy and reveal quantitative differences in dynamic intracellular activity that correlate with increased metabolic and organelle activity between phenotypes. Furthermore, we elucidate the molecular identities of structures and activity measured via UV dynamics with broad-band coherent anti-Stokes Raman scattering spectroscopy and fluorescence microscopy. We identify lipid-specific structures, and mitochondrial-specific dynamics, among other biomolecular-specific dynamic behaviors. Together, this study demonstrates deep-UV microscopy as a powerful imaging platform for probing spatial and temporally variant intracellular dynamics with biomolecular specificity, with broad implications for cell phenotyping, tissue pathology, and studying new dynamic subcellular processes.

Microscopes are essential tools for discoveries on a scale invisible to the unaided human eye. The development of immuno-fluorescence followed by molecular biology techniques and fluorescent fusion proteins have revolutionised the use of optical microscopy in bioscience. The quality of the data produced is dependent upon the sample, its preparation and the instrument used. However, instruments can degrade over time without easily visible changes to the produced images and, in turn, negatively impacts results. By testing instruments and doing comparisons between results over time and between different instruments, problems can be highlighted and corrective action can be taken. Using small fluorescent beads the point spread function (PSF) of the microscope can be recorded and the image resolution measured. Beads were prepared in a concentration matched to the field of view size and dried onto coverslips and mounted on slides. The beads were then imaged as 3D Z-stacks of sufficient size to fully enclose the PSF of the system. This data was uploaded to OMERO and processed using OMERO-metrics, an OMERO plugin developed for this purpose. This paper summarizes the development of workflows and protocols to enable this process, presents the results obtained and demonstrates the detection of significant instrument issues.

Optical coherence tomography (OCT) is widely used for retinal disease assessment, but automated quantitative analysis remains challenging because of anatomical variability and noisy imaging conditions. This study presents an interpretable OCT classification framework based on four anatomically guided retinal layers, combining preprocessing, adaptive segmentation, targeted feature engineering, and supervised classification to identify Normal, CNV, DME, and Drusen cases. Layer-specific descriptors included statistical, derivative, fluid-related, and GLCM texture markers. Feature correlation and ranking analyses showed that the proposed descriptors were highly complementary, that the most informative features were concentrated in layers 2 and 4, and that layers 1 and 3 contributed supportive structural information. Among the evaluated classifiers, the neural network performed best, achieving an accuracy of 98.17%, sensitivity of 97.88%, specificity of 99.38%, and AUC of 0.9985. Computational analysis showed efficient training and inference, with a total training time of 2216.3 s, prediction speed of approximately 160000 observations per second, and a compact model size of about 11 kB. These results demonstrated that anatomically guided feature extraction can provide accurate, efficient, and interpretable OCT disease classification, offering a practical alternative to less transparent end-to-end deep learning approaches.

We demonstrate the use of fluorescence correlation spectroscopy (FCS) to characterize fluorescently-labeled protein production. We use cell-free protein synthesis to express the protein YFP-CopB, a fusion of Chlamydia Outer Protein (Cop) B and Yellow Fluorescent Protein (YFP). CopB is a [~]50 kDa protein believed to have a critical role in chlamydial infection.1 After adding a plasmid encoding YFP-CopB to an E. coli cell-free lysate, protein expression begins. We track the cell-free reaction over several hours using the EI-FLEX, a commercial instrument with FCS capability. As protein is expressed over time, YFP-CopB increases in concentration, and the EI-FLEX detects an increase in fluorescent signal above the background of the cell-free lysate. The FCS data collected gives information about the size, aggregation tendencies, rates of production and fluorescent protein maturation, and concentration of the YFP-CopB produced. The use of FCS concurrent with cell-free synthesis presents a simple method to characterize proteins of interest as they are produced without the need for purification.

Background Tumor hypoxia and abnormal vasculature are closely associated with aggressiveness in solid tumors. Therefore, noninvasive assessment of these features in primary breast cancer is needed. Photoacoustic (PA) imaging is an emerging modality that enables real-time visualization of vascular architecture and hemoglobin oxygenation. Methods Breast PA imaging was performed in patients with primary breast cancer using a bed-type PA imaging system equipped with a hemispherical sensor and a flat specimen holder enabling mild breast compression. Three independent evaluators assessed predefined characteristics of tumor-associated vasculature: centripetal/disrupted vessels and intratumoral vessel-like signals. Oxygenation (S-factor) of tumor-associated vessels was estimated using dual-wavelength laser irradiation at 756 and 797 nm. Results PA imaging was performed in 9 tumors from 8 patients. Eight tumors were evaluable, after the exclusion of 1 tumor with segmental bloody discharge. Centripetal/disrupted vessels were identified in 7 tumors (87.5%). Intratumoral vessel-like signals were observed in all tumors (100%), with higher signal density than in surrounding tissue in 5 lesions (62.5%). Increased intratumoral signal density was associated with a higher Ki67-labeling index (two-sided P = .01). Mean intratumoral S-factor level (76.9% {+/-} 9.1%) was significantly lower than that of peritumoral vessels at 5 mm (86.4% {+/-} 5.9%) and 20 mm (88.5% {+/-} 4.9%) from the tumor margin (two-sided P < .01). Conclusion PA imaging with a flat specimen holder enables noninvasive visualization of tumor-associated vasculature with reduced oxygenation in primary breast cancer. This approach may provide a novel imaging platform for the early detection and functional assessment of breast cancer.

Urinary stone disease is a common urological condition with increasing incidence, particularly in developed countries. Laser lithotripsy (LL) has become a preferred minimally invasive treatment due to its high precision and low tissue damage. Recent studies suggest that cavitation plays a critical role in stone damage during LL, and three-dimensional passive cavitation mapping (3D-PCM) has emerged as a promising tool for detecting these events. However, clinical translation of 3D-PCM remains challenging due to limitations in imaging depth, field of view (FOV), and procedural compatibility. Here, we present a large-FOV dual-modality imaging system (3D-PCM and B-mode ultrasound) based on a large-aperture planar ultrasound array. Through array optimization and model-based reconstruction, our system achieves an expanded FOV of ~40*40mm^2 at a clinically relevant imaging depth of ~110mm, while maintaining high spatial resolution of ~0.6 mm laterally and ~0.4 mm axially. In vivo experiments in a porcine model demonstrate that the reconstructed cavitation distribution correlates well with stone damage. Our technology has the potential to provide real-time treatment feedback during LL without disrupting the standard workflow.

AO_SCPLOWBSTRACTC_SCPLOWEarly tumor detection is critical for improving patient survival and recovery. Clinically, tissue palpation is routinely used to identify regions of abnormal stiffness, a hallmark of many pathological conditions. However, palpation is restricted to anatomically accessible sites and remains highly operator dependent. Here, we introduce a method for real-time quantitative stiffness mapping using an unmodified commercial endoscope, with the goal of enhancing diagnostic capabilities and restoring mechanical feedback during endoscopic procedures. Our approach combines shear wave elastography with speckle imaging and an innovative synchronization strategy that enables the measurement of shear wave propagation using an unmodified commercial endoscope. The resulting wave fields are analyzed with the noise-correlation-inspired (NCI) method[1], providing pixel-wise estimates of shear wave velocity and, consequently, quantitative maps of local tissue stiffness. The method demonstrated robust performance in both benchtop and endoscopic configurations. Validation was achieved on polymer phantoms as well as on ex vivo and in vivo biological tissues, highlighting its potential for minimally invasive biomechanical imaging and real-time tissue characterization.

We present a non-invasive approach for continuous monitoring of lactate dynamics in-vivo using near-infrared (NIR) spectroscopy. Lactate-related spectral features were measured non-invasively within the overtone region (1600-1850 nm). Several anatomical measurement sites were evaluated, and the middle phalanx of the dorsal finger emerged as the most promising location due to its superior spectral quality and stable tissue perfusion, becoming the exclusive site for all further experiments. Across multiple exercise sessions, predictive models achieved high within-day accuracy (R2[&ge;] 0.8), while cross-day performance was affected by spectral drift and physiological variability. A dynamic offset-correction procedure effectively mitigated these baseline shifts, enabling stable prediction accuracy across days, weeks, and subjects. These findings demonstrate the feasibility of NIR-based lactate estimation and highlight the importance of adaptive correction strategies for reliable long-term, non-invasive monitoring.

Spatial frequency domain imaging (SFDI) has demonstrated the ability to provide early, quantitative assessment of burn wound severity. Previous studies using a research-grade SFDI platform showed that high-dimensional datasets incorporating multiple spatial frequencies and wavelengths can predict healing outcomes in controlled porcine models of graded burns. To assess the impact of reduced measurement dimensionality on diagnostic performance, we compared classifications derived from a research-grade SFDI system (Reflect RS) with those obtained using a simplified commercial SFDI platform (Clarifi RS). Both systems were used to image graded burns 24 hours after injury. Pixel-level classifiers were trained using regions defined by 28-day healing outcomes, and models based on the full Reflect dataset were compared with classifiers generated from reduced Reflect feature sets and datasets designed to mimic Clarifi acquisition features. Performance was evaluated using leave-one-subject-out validation. The full Reflect dataset achieved the highest classification performance, with mean F1 scores approaching 0.88. Although reducing the number of measured features decreased classification accuracy, simplified models and Clarifi-based datasets maintained F1 scores greater than 0.8 for binary classification. These findings indicate that dimensionality reduction produces a measurable but manageable loss in performance and support the development of clinically practical, application-specific SFDI systems for burn assessment.