Special Issue on Translational Biophotonics

Simultaneous recording of large-scale neural network activity in vivo is essential for unraveling fundamental processing mechanisms in the brain. For such applications, optical imaging becomes indispensable because it is minimally-invasive, allows flexible recording characteristics, and provides high signal-to-noise ratio. However, physical limitations hinder the pursuit of increasing the imaging scale, speed, and penetration depth for increasing this method’s applicability for the growing field of neuroscience. In this review, we first summarize the practical requirements and limitations in current functional imaging systems, followed by a review of the latest hardware developments to supercede current limitations, specifically for the widely adopted multiphoton microscopy. We then introduce advances in point-spread-function (PSF) engineering, i.e. the manipulation of the microscope’s PSF, and discuss the possibility of integrating computational approaches together with PSF engineering to further enhance performance. We expect that future integration of computational imaging and advanced optical methods will be adopted to meet the emerging requirements of modern neuroscience.

Photoacoustic tomography (PAT) has become a fast-evolving biomedical imaging modality in recent years. In PAT, image reconstruction is a critical step to produce high-quality photoacoustic images from raw photoacoustic signals. To date, algorithms based on back projection are the most widely used image reconstruction techniques due to their simplicity and computational efficiency. However, images reconstructed by back projection contain negative values, especially at the edge of photoacoustic sources, which have no physical meaning and are essentially undesired artifacts. In this work, we study the formation mechanism, fundamental causes and removal strategies of the negativity artifacts in back-projection-based PAT. Our results show that limited detector bandwidth and limited view angle are two fundamental causes of negativity artifacts. When the bandwidth of a detector is limited, back-projection signals will be distorted as a result of the loss of frequency contents and negativity artifacts thus appear. When the view angle of the detector is limited, photoacoustic signals propagating in three-dimensional space will be partially lost, resulting in negativity artifacts. Post-processing strategies, such as envelope detection and forced zeroing can be used to remove the negativity artifacts but may cause problems. Since negativity artifacts are a common image quality degradation factor in PAT, understanding their characteristics may expedite the development of novel artifact-removal techniques and artifact-free image reconstruction algorithms, which are of importance to correct image interpretation and quantitative imaging.

Super-resolution structured illumination microscopy (SR-SIM) has attracted a great deal of attention in the past few decades. As a wide-field imaging technique, SR-SIM usually suffers from issues relating to out-of-focus background, particularly when imaging thick samples. In this study, we develop an integrated SIM with simultaneous SR and optical sectioning (OS) capabilities, facilitating SR imaging of stacked optical sections, with the out-of-focus background suppressed. The combination of the merits of SR and OS is realized by means of a new image reconstruction algorithm. We confirm the validity of the integrated SIM, both experimentally and in simulation. We anticipate that this integrated SIM will assist biologists in obtaining much clearer SR images in relation to thick specimens.

Characterizing an ischemic brain injury at its early stage is critical to biological research and the clinical diagnosis of cerebral ischemia-related diseases. However, approaches with intravital, label-free, and real-time characterization capabilities are scarce. Two-photon excitation fluorescence lifetime imaging microscopy (FLIM) can detect variations in energy metabolism based on the autofluorescence of reduced nicotinamide adenine dinucleotide (NADH). Using this unique feature, we proposed a novel approach for cerebral ischemia characterization. From investigating cell and animal models, the cerebral NADH fluorescence lifetime was observed to be sensitive to metabolic changes caused by ischemia and consistent with ischemic time. A comparison with standard blood flow imaging and neuronal injury assessment further suggests that, the two-photon FLIM, using NADH as an indicator, can characterize degrees of cerebral ischemia and related injuries, particularly at the early stage. These findings demonstrate that NADH FLIM is promising for providing intravital, label-free, and real-time assessment of cerebral ischemia and ischemic brain injury that will be significant to the study and diagnosis of related diseases.

Respiratory rate (RR) monitoring provides crucial information on the overall health condition of patients and a reliable, low cost RR monitor for normal hospital inpatient or home use would be of significant benefit. The proposed system measures light reflection from a Fibre Bragg Grating (FBG) located near, and the total reflection spectrum from a humidity sensing film deposited at, the tip of an optical fibre. Every breath causes a shift in the wavelength reflected from the FBG and intensity change in the overall reflection spectrum. The accuracy of different techniques is investigated in a two-part study with 15 healthy volunteers. In part 1, the participants’ respiration rate followed a handheld mobile application at 5, 12 and 30 breaths per minute with simultaneous measurement using the optical fibre system, thoracic impedance pneumography (TIP) and capnometry device (where possible). Two types of medical face masks and a nasal cannula with oxygen delivery rates were investigated. In part 2, participants wore an anaesthetic face mask and breathed at normal and low tidal volumes to evaluate whether low tidal volumes could be detected. The most accurate measurement of RR was through monitoring the Bragg wavelength shift (mean accuracy = 88.1%), followed by the intensity change at the Bragg wavelength (mean accuracy = 78.9%), capnometry (mean accuracy = 77.8%), area under the overall spectrum (mean accuracy = 65.4%) and TIP (mean accuracy = 43.1%). The Fibre-optic Respiratory Rate Sensor system (FiRRS) can differentiate between normal and low tidal volumes (p-value < 0.05) and demonstrated higher accuracy than capnometry measurement of end-tidal carbon dioxide in exhaled air. These latter two monitors measured RR more accurately than TIP. A comparable accuracy in the measurement of RR was obtained when the FiRRS was implemented in nasal cannula and face masks.

A two-camera fluorescence system for indocyanine green (ICG) signal detection has been developed and tested in a clinical feasibility trial of ten patients, with a resolution in the submillimetre scale. Immediately after systemic ICG injection, the two-camera system can detect ICG signals in vivo (∼2.5 mg ${{\text{l}}^{ - 1}}$ or 3.2 × ${10^{ - 6}}{ }$ M). Qualitative assessment has shown that the fluorescence signal does not always correlate with the cancer location in the surgical scene. Conversely, fluorescence image texture metrics when used with the logistic regression model yields good accuracy scores in detecting cancer. We have demonstrated that intraoperative fluorescence imaging for resection guidance is a feasible solution to tackle the current challenge of positive resection margins in breast conserving surgery.

Developing a high-resolution non-invasive optical coherence tomography angiography (OCTA) method for iris vasculature imaging is essential for diagnosing a wide range of ocular pathologies. However, the current iris-OCTA devices are still limited in imaging quality and penetration depth for dark-colored eyes ranging from brown to dark brown. A spectral domain iris-OCTA system is presented in this paper incorporating a 1300 nm wavelength for deeper tissue penetration, a linear-wavenumber spectrometer for better detection sensitivity, and an iris scan objective lens for better optical focusing across the entire iris over a 12 × 12 mm² scan field. The −6 dB fall-off range is ∼3 mm, and the maximum sensitivity fall-off is −28.57 dB at 6.94 mm. The axial resolution is 15.1 ± 3.2 μm. The 40 mm focal-length iris scan objective is optimized based on the ocular parameters from 100 Asian participants’ left eyes, and it has a diffraction-limited lateral resolution (14.14 μm) for the iris, in general. OCT distortions were calibrated based on the average ocular parameters, and the maximum residual distortions in both the lateral and axial directions were <0.1 mm (2.0%) for all of the eyes. A pilot study on a constricted pupil was performed to demonstrate high-contrast, wide-field en face iris microvascular imaging by either a horizontal or vertical fast-scan protocol in a dark brown eye. The iris vessels are radially aligned, and each vessel is more visible when it has an angle of ∼65°–90° with respect to the fast-scan direction. A new circular fast-scan protocol could improve image quality for better visualization of the iris features or integration with image-registration algorithms and an eye-tracking system for eye-motion compensation.

We present a new instrumental and computational pipeline named FAMOUS: fast algorithm for three-dimensional (3D) multiphoton microscopy of biomedical structures. This pipeline rests on a MPM strategy combined with an original 3D post-processing computational approach. In the present work, FAMOUS approach is devoted to the 3D imaging of the myosin assembly of the ultrastructure of a whole striated skeletal muscle unsliced. Raw recordings of second harmonic generation (SHG) from myosin and instrumental point-spread functions (PSF) are led simultaneously all along the unsliced muscle depth. This procedure highlights a space-variant distortion of the PSF and the SHG signals, and an optical degradation of the axial resolution increasing with imaging depth resulting from the optical heterogeneity of the muscle structure. A 3D mathematical modelling of the PSF, relying on the recent FIGARO method, evaluates and models the depth-variant evolution of the optical distortions. Then, the fast image deblurring algorithm BD3MG is employed to correct those non-stationary distortions all along the sample, thanks to a sounded regularized inverse problem methodology. This leads to the pipeline called FAMOUS, whose performance are highlighted for the optimization of the axial information of myosin structure, whose dimensions are close to the axial resolution limit. For the first time, the 3D organization of the myosin in skeletal muscle is visually shown from an unsliced whole muscle, starting with a solution of optical microscopy. The axial visualization of this organization presently disclosed were never shown until now without a preliminary procedure of sample slicing and labelling. Our original solution FAMOUS delivers a new point of view of this biological structure in the 3D and especially in the optical axis. Image information theoretically expected are now revealed visually in the optical axis for the first time in a whole organ unsliced and label free.

Despite advances in intraoperative surgical imaging, reliable discrimination of critical tissue during surgery remains challenging. As a result, decisions with potentially life-changing consequences for patients are still based on the surgeon’s subjective visual assessment. Hyperspectral imaging (HSI) provides a promising solution for objective intraoperative tissue characterisation, with the advantages of being non-contact, non-ionising and non-invasive. However, while its potential to aid surgical decision-making has been investigated for a range of applications, to date no real-time intraoperative HSI (iHSI) system has been presented that follows critical design considerations to ensure a satisfactory integration into the surgical workflow. By establishing functional and technical requirements of an intraoperative system for surgery, we present an iHSI system design that allows for real-time wide-field HSI and responsive surgical guidance in a highly constrained operating theatre. Two systems exploiting state-of-the-art industrial HSI cameras, respectively using linescan and snapshot imaging technology, were designed and investigated by performing assessments against established design criteria and ex vivo tissue experiments. Finally, we report the use of our real-time iHSI system in a clinical feasibility case study as part of a spinal fusion surgery. Our results demonstrate seamless integration into existing surgical workflows.

In this report, we report on the implementation of compressive sensing (CS) and sparse sampling in polarization sensitive optical coherence tomography (PS-OCT) to reduce the number of B-scans (frames consisting of an array of A-scans, where each represents a single depth profile of reflections) required for effective volumetric (3D dataset composed of an array of B-scans) PS-OCT measurements (i.e. OCT intensity, and phase retardation) reconstruction. Sparse sampling of PS-OCT is achieved through randomization of step sizes along the slow-axis of PS-OCT imaging, covering the same spatial ranges as those with equal slow-axis step sizes, but with a reduced number of B-scans. Tested on missing B-scan rates of 25%, 50% and 75%, we found CS could reconstruct reasonably good (as evidenced by a correlation coefficient >0.6) PS-OCT measurements with a maximum reduced B-scan rate of 50%, thereby accelerating and doubling the rate of volumetric PS-OCT measurements.

We investigate changes in optical coherence tomography (OCT) images in response to evoked neural activity in the sciatic nerve of rats in vitro. M-scans were obtained on peripheral nerves of rats using a swept source polarisation sensitive OCT system, while a nerve cuff acquired electrical neural recordings. From a total of 10 subjects: three had no stimulation (controls), three had paw stimulation, and four had nerve stimulation. Changes in the OCT signal intensity, phase retardation, phase, and frequency spectra were calculated for each subject and reference samples of a mirror and microspheres in solution. Observed changes in intensity in three paw stimulation and two nerve stimulation subjects and changes in frequency spectra amplitude in two paw stimulation subjects were above the reference noise level and were temporally consistent with osmotic swelling from ion currents during neural activity. Light scattering changes produced by osmotic swelling, which have previously been characterised in squid and crab nerves, are also thought to occur in myelinated fibres on a scale which is detectable using OCT. Imaging neural activity in myelinated tissue using OCT creates new possibilities for functional imaging in the peripheral and central nervous systems.

Alzheimer’s disease (AD) has become one of the most worrying health conditions with no effective treatment available with the increase in population aging. A large number of clinical studies and experiments proved that photobiomodulation (PBM) had a positive effect on AD treatment. The irradiation with red and near-infrared light at a low dose can effectively reduce an accumulation of amyloid-β (Aβ) plaques in the central nervous system, relieving the symptoms of AD. This review summarizes the parameters of PBM for AD treatment studied on cells, animals, and in clinical trials, as well as the dose–effect relationship of PBM treatment for AD. The mechanisms of PBM on the cellular level, which include regulation of microglia and astrocytes that may affect Aβ plaque elimination are also discussed.

Clinical transplantation medicine currently faces a significant shortage of organ donors to supply the need of an increasingly aged population. Despite this, organs are still discarded due to graft stress induced by hypoxia or ischemia prior to procurement. Approaches to minimize donor organ discard include appropriate organ preservation and monitoring of organ function. Predominant organ preservation strategies involve hypothermia between 0 °C and 12 °C. In this study, we investigate the effect of temperature alone on tissue microstructural and biochemical parameters during cold preservation of mouse organs. To the best of our knowledge, this is the first study evaluating this cooling effect on multiple tissue parameters such as blood oxygenation, concentrations of blood, methemoglobin, water, lipid, and bile as well as scattering amplitude, Mie scattering power and fraction of Rayleigh scattering. These parameters were extracted by using diffuse reflectance spectroscopy spectral fitting at an extended wavelength range between 450 and 1590 nm and a Monte Carlo look-up table including a wide range of tissue optical properties compared to previous studies. Our findings can be used to understand biological processes undertaking cooling to propose new strategies involving optimized cold storage times and composition of organ preservation solutions for minimized cellular and tissue damage.

Gastric cancer, one of the most common malignant tumors that can affect the digestive system, poses a serious threat to human life. The survival rate of gastric cancer patients depends on early detection and treatment. The widespread adoption of endoscopy has improved the detection rate of early gastric cancer. Accurate preoperative diagnosis of early gastric cancer is key to developing individualized treatment strategies. Here, nonlinear optical microscopy (NLOM) is used to differentiate between normal gastric mucosae and those with early gastric cancer. Furthermore, the quantitative relationship between submucosal infiltration depth and collagen signals in early gastric cancer is explored. First, the two-dimensional collagen direction angle was measured as an indicator to identify cancerous tissue. The orientation indexes of collagen fibers in normal and cancerous tissues were found to be 0.8511 ± 0.0839 and 0.6466 ± 0.07429 (P < 0.0001), respectively, indicating a significant decrease for the cancerous site. The backscattered second harmonic generation (SHG) signal corresponding to the collagen content and the three-dimensional collagen fiber orientation were then studied for early gastric cancer at different infiltration depths. The backscattered collagen SHG signal (a.u.) in the infiltrated lamina propria, muscularis mucosa, and submucosa were found to be 0.1850 ± 0.0393, 0.0870 ± 0.0189, and 0.0435 ± 0.0163, respectively. The 3D directional variance of collagen corresponding to the three infiltration depth sites were 0.6108 ± 0.0707, 0.6794 ± 0.0610, and 0.8200 ± 0.0618 (P < 0.05), respectively. Significant differences between the early gastric cancer collagen signals at different infiltration depths were observed. Our results indicate that NLOM can differentiate cancerous tissue from normal tissue, and thus diagnose early gastric cancer based on infiltration depth. NLOM provides a new evaluation method for the real-time in situ diagnosis of early gastric cancer and has important clinical significance for preparing accurate individualized treatment guidance.

We demonstrate a deep learning based contact imaging on a CMOS chip to achieve ∼1 μm spatial resolution over a large field of view of ∼24 mm². By using regular LED illumination, we acquire the single lower-resolution image of the objects placed approximate to the sensor with unit fringe magnification. For the raw contact-mode lens-free image, the pixel size of the sensor chip limits the spatial resolution. We apply a super-resolution generative adversarial networks, a type of deep learning based single-image super-resolution (SR) algorithm, to circumvent this limitation and effectively recover much higher resolution image of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area, which is also equivalent to the imaging field-of-view (24 mm²) due to unit magnification. This SR contact imaging approach eliminates the need of either lens or multi-frame acquisition, being very powerful and cost-effective. We demonstrate the success of this approach by imaging the proliferation dynamics of large-scale cells and the Instantaneous behaviors of freely moving Caenorhabditis elegans directly on the chip.

HiLo microscopy is a wide-field, optical-sectioning imaging technique, which is based on computational reconstruction from a uniform-illumination image and a structured-illumination (SI) image. Considering different imaging situations, the parameters of SI patterns should be optimized. However, no such discussion has been presented in grid-pattern (such as sinusoidal pattern and checkerboard pattern) based HiLo microscopy. Here, we analyze the dependence of optical-sectioning performance on parameters of SI pattern via both numerical simulations and imaging experiments. We find that both lower frequency and lower duty cycle of the grid-based pattern would introduce higher modulation depth, which would induce less artifacts in final reconstruction. Besides, at given illumination wavelength and objective numerical aperture, the higher the frequency of the grid-based pattern is, the better the axial resolution is, and thus the better the contrast of the optical-sectioning image is. Specially, the axial resolution is optimal when the frequency of pattern is set to half of cut-off frequency. We expect it as a guide of optimizing parameters of SI patterns for optical-sectioning in HiLo microscopy.

A Mueller matrix can completely characterize the polarimetric properties of a medium, where the parameters of depolarization, retardance and diattenuation can be obtained by decomposing a Mueller matrix with existing decomposition methods. The introduction of polarization sensitive cameras with integrated wire-grid polarizers has allowed for the fast acquisition and analysis of four linear states within a single snapshot. Moreover, these cameras provide the opportunity to capture a reduced 3 × 4 Mueller matrix with the acquisition of generated states polarization in the illumination arm. In order to measure and characterize samples using a reduced 3 × 4 Mueller matrix, a 3 × 4 decomposition algorithm is introduced. This new algorithm is compared and validated against established 4 × 4 decompositions. The validation of this algorithm is shown using a previously reported Mueller matrix of polyacrylamide phantom, and experimental Mueller matrices of quarter-wave plates, silicone phantoms and a skin model sample. The 3 × 4 decomposition compares well to established decompositions and is capable of characterizing the samples based on the calculation of depolarization, retardance and orientation.

Colorectal cancer (CRC) is the 3rd most common and the 2nd most deadly type of cancer worldwide. Understanding the biochemical and microstructural aspects of carcinogenesis is a critical step towards developing new technologies for accurate CRC detection. To date, optical detection through analyzing tissue chromophore concentrations and scattering parameters has been mostly limited to chromophores in the visible region and analytical light diffusion models. In this study, tissue parameters were extracted by fitting diffuse reflectance spectra (DRS) within the range 350–1900 nm based on reflectance values from a look-up table built using Monte Carlo simulations of light propagation in tissues. This analysis was combined with machine learning models to estimate parameter thresholds leading to best differentiation between mucosa and tumor tissues based on almost 3000 DRS recorded from fresh ex vivo tissue samples from 47 subjects. DRS spectra were measured with a probe for superficial tissue and another for slightly deeper tissue layers. By using the classification and regression tree algorithm, the most important parameters for CRC detection were the total lipid content (f_lipid), the reduced scattering amplitude (α′), and the Mie scattering power (b_Mie). Successful classification with an area under the receiver operating characteristic curve higher than 90% was achieved. To the best of our knowledge, this is the first study to evaluate the potential tissue biomolecule concentrations and scattering properties in superficial and deeper tissue layers for CRC detection in the luminal wall. This may have important clinical applications for the rapid diagnosis of colorectal neoplasia.

Histopathology currently acts as a gold standard for human prostate cancer (PCa) diagnosis. However, the subjective nature of histopathology leads to inevitable discordance among pathologists. Specifically, the inter-observer discordance could be up to 40% for the differentiation between Gleason score 6 (low-grade) and 7 (high-grade) of PCa. According to clinical guidelines, patients with high-grade PCa need to be actively treated, while patients with low-grade PCa could undergo active surveillance due to its slowly growing feature. Therefore, differentiating high-grade and low-grade PCa is an urgent clinical need. By integrating stimulated Raman scattering microscopy and confocal Raman spectroscopy, our previous study found the aberrant cholesteryl ester (CE) accumulation in human PCa tissues. However, no significant difference in CE accumulation between the low-grade and high-grade PCa was found, primarily because the previous study only analyzed the composition of manually selected lipid droplets (LDs) without quantitative analysis of the whole field of view. Here, we employed hyperspectral stimulated Raman scattering (HSRS) microscopy to test the hypothesis of CE as a marker for differentiation of low-grade and high-grade human PCa. First, lipid, lipofuscin, and protein were quantitatively mapped in human prostate tissues based on HSRS imaging of C–H vibrational region and multivariate curve resolution analysis. Then, within the lipid channel, CE percentage and unsaturation level of LDs were quantitatively mapped according to the height ratio between Raman bands at 2870 and 2850 cm⁻¹, and between Raman bands at 3006 and 2850 cm⁻¹, respectively. In total of 6 normal prostate tissues, 9 low-grade and 9 high-grade PCa tissues from patients, we found lipofuscin accumulation in all the normal prostate but none in PCa. While all the high-grade PCa tissues had LD accumulation, only 3 low-grade PCa tissues had LD accumulation. Notably, among all the PCa tissues with LD accumulation, no significant difference in LD amount was found between low-grade and high-grade PCa. Fortunately, both CE percentage and unsaturation level of the LDs were significantly different between low-grade and high-grade PCa. Furthermore, it was shown that CE percentage could differentiate low-grade and high-grade PCa with high sensitivity and specificity. Taken together, our study may provide a new opportunity towards more accurate PCa diagnosis.

Many biomedical applications require measurements of Raman spectra of tissue under ambient lighting conditions. However, the background light often swamps the weaker Raman signal. The use of time-gated (TG) Raman spectroscopy based on a single photon avalanche diode (SPAD) operating in time-correlated single photon counting and near-infrared laser excitation was investigated for acquisition of Raman spectra and spectral images of biological tissue. The results obtained using animal tissue samples (adipose tissue and muscle) show that the time gating modality enables measurement of Raman spectra under background light conditions of similar quality as conventional continuous wave Raman spectroscopy in the absence of background light. Optimal suppression of the background light was observed for time gate widths of 300–1000 ps. The results also showed that TG Raman spectroscopy was able to detect subtle spectral differences required for medical diagnostics, such as differences in Raman spectra of cancer and normal tissue. While the current instrument required scanning of the grating in order to obtain full Raman spectra, leading to impractical times for multi-wavenumber Raman mapping, imaging time could be drastically reduced by spectral multiplexing (compressed detection) using digital micromirror devices or by using SPAD arrays.

A Mueller matrix is a comprehensive representation of the polarization transformation properties of a sample, encoding very rich information on the microstructure of the scattering objects. However, it is often inconvenient to use individual Mueller matrix elements to characterize the microstructure due to a lack of explicit connections between the matrix elements and the physics properties of the scattering samples. In this review, we summarize the methods to derive groups of polarization parameters, which have clear physical meanings and associations with certain structural properties of turbid media, including various Mueller matrix decomposition (MMD) methods and the Mueller matrix transformation (MMT) technique. Previously, experimentalists have chosen the most suitable method for the specific measurement scheme. In this review, we introduce an emerging novel research paradigm called ‘polaromics’. In this paradigm, both MMD and MMT parameters are considered as polarimetry basis parameters (PBP), which are used to construct polarimetry feature parameters (PFPs) for the quantitative characterization of complex biomedical samples. Machine learning techniques are involved to find PFPs that are sensitive to specific micro- or macrostructural features. The goal of this review is to provide an overview of the emerging ‘polaromics’ paradigm, which may pave the way for biomedical and clinical applications of polarimetry.

Intraoperative Thermal Imaging (ITI) is a new minimally invasive diagnosis technique that can potentially locate margins of brain tumor in order to achieve maximum tumor resection with least morbidity. This study introduces a new approach to ITI based on artificial tactile sensing (ATS) technology in conjunction with artificial neural networks (ANN) and feasibility and applicability of this method in diagnosis and localization of brain tumors is investigated. In order to analyze validity and reliability of the proposed method, two simulations were performed. (i) An in vitro experimental setup was designed and fabricated using a resistance heater embedded in agar tissue phantom in order to simulate heat generation by a tumor in the brain tissue; and (ii) A case report patient with parafalcine meningioma was presented to simulate ITI in the neurosurgical procedure. In the case report, both brain and tumor geometries were constructed from MRI data and tumor temperature and depth of location were estimated. For experimental tests, a novel assisted surgery robot was developed to palpate the tissue phantom surface to measure temperature variations and ANN was trained to estimate the simulated tumor’s power and depth. Results affirm that ITI based ATS is a non-invasive method which can be useful to detect, localize and characterize brain tumors.

Optical coherence tomography (OCT) systems have huge potential for applications beyond the traditional ophthalmology as a general-purpose medical instrument for optical biopsy. The widening of the range of applications is expected to significantly increase production volume and, consequently, puts pressure on unit cost. This trend calls for a flexible and miniaturized system fabricated in a batch process. In this paper, the different OCT configurations are compared for suitability in such an implementation. The required flexibility favors operation in the spectral domain, using a broadband light source in combination with a spectrometer, while the miniaturization and low unit-cost in batch fabrication can be achieved using silicon micro-system technologies. The feasibility of miniaturizing OCT components has already been demonstrated, amongst others a beam splitter using 45° saw dicing of a glass substrate and appropriate thin-film coating the integration of the essential components into a single OCT microsystem remains a challenge. In this paper, the wafer-level fabrication of a Michelson interferometer for a miniaturized OCT system is presented, using an improved 45° saw dicing process, which is suitable for wafer-level co-integration of also the other components of the OCT microsystem.

A well-trained deep neural network is shown to gain the capability of simultaneously restoring two kinds of images, which are completely destroyed by two distinct scattering media, respectively. The network, based on the U-net architecture, can be trained by a blended dataset of speckles-reference images pairs. We experimentally demonstrate the power of the network in reconstructing images which are strongly diffused by a glass diffuser or multi-mode fiber. The learning model further shows good a generalization ability to reconstruct images that are distinguished from the training dataset. Our work facilitates the study of optical transmission and expands machine learning’s applications in optics.

This paper demonstrates a microwave biosensor, based on the spoof surface plasmon polaritions (SSPPs) excited by a planar plasmonic waveguide, which can measure in vivo the water content of human skin tissues timely and accurately. A SSPPs biosensor is fabricated and measured using the vector network analyzer using a human finger as a real model. Experimental results of the biosensor with/without normal human finger skin tissues and pure water have a good agreement with our simulation. The SSPPs biosensor has potential applications for the areas of in vivo measurement of the human stratum corneum water content with topical cosmetics, early diagnostics of superficial tumors such as malignant melanoma and lymphatic cancer, and also in the guiding tumors resection.

Schwannoma is a kind of slow-growing and rare neoplasm which poses diagnostic challenges owing to its clinical silence at the presentation period. Here, a schwannoma tumor was studied by multiphoton microscopy (MPM). Results indicate that MPM is capable of identifying a schwannoma tumor without the need for labels. Based on the two-photon excited fluorescence signals from cells and blood vessels and second harmonic generation signals from collagens, several significant features for the identification of schwannoma were visualized, including the Antoni A region, Antoni B region, pericellular collagen pattern, hyalinized vessels and hyalinized stroma. These conclusions highlight the potential of MPM taken as a diagnostic method for label-free identification of schwannoma tumors by these histopathologic characteristics.