This PDF file contains the front matter associated with SPIE Proceedings Volume 12367, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

Cross-sectional 4-D imaging of vocal fold morphology and function is desirable for accurate diagnosis of many vocal fold pathologies, which occur throughout the epithelial layer and alter the mucosal wave. Clinical videoendoscopy provides qualitative diagnostic information but remains limited to surface visualization of layered vocal fold structure and two-dimensional mucosal vibration. While OCT has been investigated to address the shortcomings of standard 2-D endoscopy, challenges remain in reconstruction of the 4-D mucosal wave over the entire vocal fold structure. To address these challenges, we have developed a fast-scanning OCT laryngoscope to enable asynchronous Nyquist sampling of the human voice fundamental frequency range (and its harmonics, up to 1 kHz). We present a new algorithm for reconstruction of the 4-D vocal fold dynamics during phonation using OCT volume data of the entire anterior-posterior vocal fold structure. Reconstruction of the vibration of a vocal fold phantom confirmed feasibility of the algorithm and preliminary reconstruction of the in vivo vocal fold glottal cycle is presented. This work represents the first cross-sectional Nyquist sampling of the in vivo human mucosal wave using an OCT system with hardware capable of encompassing the human fundamental frequency range (i.e., 90-260 Hz). The developed OCT laryngoscope and algorithm will enable volumetric representations of vocal fold dynamics in the clinic and development of quantitative metrics for diagnostic and interventional guidance.

High-speed endoscopic optical coherence tomography (OCT) imaging in the MHz range has shown great potential in various medical applications ranging from cancer screening to vascular disease monitoring. High-speed imaging always suffers from non-uniform rotational distortion (NURD) due to asynchronous motor rotation with the OCT system. Several research groups have previously attempted to solve this problem, using either an expensive motor with a sensor or numerical correction after data acquisition. However, both techniques pose challenges for practical use. Therefore, in this study, we use an inexpensive sensorless brushless DC motor with a Fourier domain mode-locked (FDML) laser-based MHz OCT system and try to resolve the problem of synchronization using three different modalities, (i) Slave-mode: The FDML frequency serves as a master frequency for the motor, which is phase-locked to the FDML frequency, (ii) Master-mode: The revolution trigger obtained from the motor’s back electromotive force (BEMF) signal serves as a trigger signal for the OCT imaging system, (iii) Both: Fully synchronized setup, where the motor rotation is synchronized with the laser and the imaging system is synchronized with the motor to achieve phase-stable OCT imaging. The first case slightly fluctuates in live preview and imaging due to the absence of a revolution trigger, while the second has varying motor speeds. Therefore, we use the third case to phase-lock the motor with FDML and get a distortion-free live preview and image acquisition. Finally, we demonstrate high-speed SS-OCT structural imaging (at 3.3 MHz A-scan rates) of a finger with a 16 mm diameter probe (at 40,000 rpm).

In this report, a swept source optical coherence tomography (SS-OCT) instrument, equipped with a novel, multi-MHz tuning range swept source is presented. The source, based on an electrically pumped Micro Electro Mechanical System Vertical Cavity Surface Emitting Laser (MEMS-VCSEL) technology, is able to operate at 1.6 MHz with bidirectional sweeping, and emits light at a central wavelength of 1060 nm with a wavelength tuning range of 30 nm at -3 dB. The capabilities of the SS are investigated, and characterized, using an OCT instrument equipped with pupil tracking capabilities. The source provides an experimental axial resolution of 30 μm measured in air. From measuring the sensitivity drop-off, an axial imaging range longer than 90 mm was inferred. To estimate the wavenumber tuning non-linearities of the source and generate images, the Complex Master-Slave (CMS) method was employed. CMS also allowed for real-time visualization of the en-face images of the human retina, in-vivo, without computing the whole volume. By using the novel SS, in-vivo real-time images of the human retina are produced at 4 Hz volume rate when paired with a 2-D orthogonal galvanometer scanner. The increase in speed for A-scan and volume acquisition tends to reduce fragmented and blurry images. Apart from a montage of en-face images generated in real-time from various axial positions, we also present Bscans produced with a galvanometer scanner driven at 1 kHz from the optic nerve area.

We demonstrate a Fourier domain mode locked (FDML) laser centered around 850 nm with a sweeping range of 50 nm, a fundamental repetition rate of 2×416 kHz and an output power of 2 mW. A new cavity design using three chirped Fiber Bragg gratings is required to overcome sweeping limitations caused by high dispersion. Other solutions to address challenges such as high loss and high polarization mode dispersion will be discussed along with performance. A main application of this laser will be retinal imaging, but it might also be applicable for TiCo-Raman and SLIDE microscopy.

A MHz akinetic swept source is demonstrated by incorporating a commercial Erbium Doped Fiber Amplifier into a fiber laser cavity assembly. Such laser is brought into mode-locking based on nonlinear polarization rotation (NPR). After the laser, a dispersion compensating fiber is employed to time-stretch the broadband pulses obtained. Different cavity lengths are evaluated, leading to sweeping rates from 0.9 MHz to 9.65 MHz. A maximum of 67 nm bandwidth has been achieved. The swept source has been characterized using a Master-Slave procedure, obtaining an almost linear sweep.

We demonstrate a Fourier domain mode locked (FDML) laser centered at 1190 nm with 2×410 kHz sweep repetition rate, a sweeping range of 100 nm and 2.5 mW output power. The laser is based on a quantum dot-semiconductor optical amplifier with small linewidth enhancement factor. The laser could be used as a probe laser in stimulated Raman scattering microscopy and it may be attractive for optical coherence tomography due to low water absorption and the spectral signature of lipids around 1200nm. Moreover, it is ideal to close the gap between FDML lasers at 1064 nm and 1300 nm. Combining these three lasers can enable ultrawideband sweeping to improve the axial OCT resolution down to 2 μm.

In this summary, a fully akinetic FDML-like or so-called dual resonance sweeping regime, for swept source optical coherence tomography, SS-OCT, at 1550 nm is demonstrated. Instead of modulating the optical amplifier gain reported in our previous studies, here we employ a fiber intensity modulator as a mode-locking element. A chirped fiber Bragg grating is used to provide sufficient dispersion in the laser cavity. A tuning range of 25 nm is obtained for a sweep frequency of ≈ 900 kHz with a 6 dB drop-off in sensitivity at 2.6 mm optical path difference. Similarities in operation with the FDML concept are presented.

Ophthalmic surgery is conventionally performed under white-light microscopy which has limited benefit for identifying tissue layers and providing depth-resolved feedback. Intraoperative optical coherence tomography (iOCT) has enabled depth-resolved intraoperative imaging of retinal microstructures. Recent advancements have enabled faster imaging speeds and video-rate, volumetric iOCT imaging of surgical dynamics, and en face retinal imaging that enables robust visualization of surgical instruments for tool-tracking. Here, we demonstrate our intraoperative spectrally encoded coherence tomography and reflectometry imaging (iSECTR) system with enhanced optical throughput and mechanical focus-adjust in a more clinically robust form-factor. iSECTR uses spatiotemporally co-registered multimodal spectrally encoded reflectometry (SER) and OCT for automated en face instrument-tracking and volumetric visualization of surgical dynamics. Here, we demonstrate several optical and optomechanical design improvements, which include the design of a modular aluminum skeleton to house SECTR imaging optics and optomechanics throughput to maintain system alignment and imaging performance. Mechanical focusing capabilities were integrated to accommodate for any adjustments to surgical oculars made by the ophthalmic surgeon before surgery for simultaneous optimal imaging in both iSECTR and the ocular view of the surgical field. We demonstrate ex vivo cornea and retinal imaging, and mechanical focusing capabilities using a stationary model eye and stepping through ± 10 diopters focal shift. We predict the addition of focusing capabilities and improvements in form-factor and optical throughput to our iSECTR system will benefit surgical translation and workflow for ophthalmic surgeries.

We show number fluctuations dynamic light scattering optical coherence tomography (OCT) for measuring extremely slow, sub-diffusion flows of dilute particle suspensions. Our method removes the minimum measurable velocity limitation of conventional correlation-based or phase-resolved Doppler OCT, set by flowing particles’ Brownian motion. Our technique works for any Doppler angle, is applicable to 2D flow imaging with scanning OCT systems and can be used to determine concentration of particles under flow.

We show scanning dynamic light scattering optical coherence tomography (OCT) omnidirectional flow measurements. Our method improves the velocity measurement limit over conventional correlation-based or phaseresolved Doppler OCT by more than a factor of 2. Our technique is applicable without a-priori knowledge of the flow geometry as our method works both for non-zero Doppler angle and non-ideal scan alignment. In addition, the method improves the particle diffusion coefficient estimation for particles under flow.

Optical coherence tomography (OCT) is a powerful imaging technique to non-invasively differentiate between healthy skin and pathological conditions. Unfortunately, commercially available OCT-systems are typically slow and not capable of scanning large areas at reasonable speed. Since skin lesions may extend over several square centimeters, potential inflammatory infiltrates remain undetected. Here, we present large area robotically assisted OCT (LARA-OCT) for skin imaging. Therefor a collaborative robot is combined with an existing, home-built 3.3 MHz-OCT-system and for surface tracking an online probe-to-surface control is implemented which is solely based on the OCT surface signal. It features a combined surface-distance and surface-orientation closed-loop control algorithm, which enables automatic positioning and alignment of the probe across the target while imaging. This allows to acquire coherent OCT images of skin areas beyond 10 cm².

Optical coherence tomography (OCT) has steadily increased in scope with new applications continuing to arise. However, a major obstacle to the more widespread use of OCT is the limited scan area that can be achieved. In recent years, OCT systems using 3D eye tracking technologies and robotic arms for automatic detection and alignment of an OCT imaging system with a patient’s eye in ophthalmology have been demonstrated. This has enabled OCT without the need for precise manual alignment and stabilization of patients in ophthalmology. For non-clinical and low-cost applications, however, simple and compact automatically aligning OCT systems still need to be developed. In this work, a high-speed automatically aligning tabletop OCT beam scanning device with a simple and compact design incorporating a stereo camera and a high-speed translation stage is presented. The device automatically detects regions of interest on a sample in a 7.5×7.5cm area above the scanner, locates their three-dimensional position, and performs a synchronous alignment and scanning procedure to obtain high-quality OCT data from multiple regions at high speed. The acquisition of epidermal and dermal fingerprints for OCT-based fingerprint recognition is demonstrated. Four fingers on a user’s hand are detected, located in three-dimensional space and sequentially scanned in less than 2.3s, with the potential for scan times as low as 1.3s with faster lasers. It is envisioned that this compact tabletop scanner will enable a variety of applications in biometrics, dermatology and non-destructive testing where the high-speed acquisition of high-quality tomographic images with a compact device is desirable.

Optical coherence tomography (OCT) has been utilized to investigate the optical properties of tissue in animal model studies. Polarization sensitive OCT (PS-OCT) is one of the functional extensions of OCT, which provides additional contrasts such as birefringence and degree-of-polarization uniformity (DOPU). It enables multi-contrast imaging for discrimination of tissue properties in biological samples. However, biological samples often exhibit multiple scattering (MS). It severely hampers the penetration depth and degrades the optical property measurement in deep regions for both OCT and PS-OCT. In a recently presented work, it was found that all of the scattering OCT value, birefringence value, and DOPU value were altered if they were measured at the deep region. This alteration is suspected to be artifacts caused by MS. So far, various methods have been proposed to tackle the MS issue. One is averaging several images with decorrelated MS signals. The decorrelation of MS signals was realized by wavefront shaping with complex devices such as spatial light modulators or deformable mirrors. However, these optics increase the cost and system complexity, and the wavefront shaping is still challenging. Simple hardware, such as multimode fiber, was only demonstrated in full-field OCT. In this work, we present a method termed as “multi-focus averaging” (MFA) to suppress the MS effect and improve the image contrast in deep regions of scattering samples. It uses focus modulation by a tunable lens to decorrelate MS signals among multiple acquisitions, and computational refocusing is used to cancel the different defocus during focus modulation. The refocused OCT signals are averaged in complex to reduce MS signals. It is demonstrated in standard OCT scheme, and a scattering phantom and a post-mortem zebrafish are used to validate the intensity contrast improvement. Results show that MFA images can provide better intensity contrast than standard complex averaging in scattering samples. In addition, we further adapt this method to PS-OCT to suppress the MS and to improve the accuracy of polarization sensitive measurement. We found MFA mitigated low-DOPU artifact in polarization sensitive measurement.

A real-time high-speed line-field optical coherence tomography (LFOCT) configuration at 5,000 B-frames or 2,500,000 A-lines per second for clinical applications is described. The development of the LFOCT technology has experienced increasing interest despite the challenge of achieving sufficient sensitivity and resolution due to crosstalk. Publications of research systems usually apply expensive infrared cameras to improve image quality. The costs, complexity, and lack of real-time data transfer of dedicated highspeed IR cameras make it challenging to employ LFOCT for a more comprehensive application range. We demonstrate using a comparatively low-cost, high-speed camera for real-time data transfer and image display in conjunction with a light source at a center wavelength of 840 nm and a bandwidth of 50 nm. Although the camera and available sample power limits the sensitivity (75 dB), we can demonstrate imaging on a human fingertip (in vivo) and the cornea of a rabbit eye. Further development of the system will focus on compensating for the camera's limited sensitivity and improving resolution to target clinical in vivo imaging such as ophthalmic applications.

Full field optical coherence tomography (FF-OCT) utilizes low coherence gate to suppress the out-of-focus scattering light. The spatial resolution remains limited by numerical aperture of objective and bandwidth of light source. Structured illumination microscopy not only is a wide-field three-dimensional imaging modality which shift high spatial frequency components to optical transfer function of system, but also enables optical sectioning in biological tissue. Thus, we propose a structured illumination based FF-OCT(SI-FF-OCT) to realize three-dimensional sub-cellular resolution using parallel coded digital micromirror device (DMD). First, the principle of SI-FF-OCT was introduced in terms of point spread function (PSF) of the standard FF-OCT optical system. Second, a 1D illumination pattern of SI-FF-OCT for imaging random tissue was simulated for both of lateral resolution enhancement and optical sectioning capacity in the same configuration. The results of onion cells and mouse liver tissue suggested that the proposed white-light structured illumination approach in FF-OCT demonstrates tomographic imaging for thick transparent samples with a higher lateral resolution and better contrast than standard FF-OCT. As a benefit of the fringe projection and low-coherence gate filtering, SI-FF-OCT also has optical sectioning capability in free of speckle-noise in sub-pixel accuracy way.

To image the underlying structures of a scattering medium, raster scanning imaging technologies capture least scattered photons (LSPs) and reject multiple scattered photons (MSPs) in backscattered photons. However, MSPs can still squeeze into the images, resulting in limited imaging depth, degraded contrast, and significantly reduced lateral resolution. Great efforts have been made to understand how MSPs affect imaging performance through modeling, but how the backscattered photons are distributed in a scattering medium during imaging remains a conceived picture base on simulations. Here, we demonstrate a method of reconstructing BSPP using beam-offset optical coherence tomography (OCT), where OCT images are acquired at offset positions from the illumination beam. By separating LSPs and MSPs, we can quantify imaging depth, contrast, and lateral resolution and access the depth-resolved modulated transfer function (MTF). This approach presents great opportunities for better retrieving tissue optical properties, correctly interpreting images, or directly using MTF as the feedback for adaptive optical imaging.

Optical coherence tomography (OCT) image quality is sensitive to eye movements during image acquisition. Image registration is a common approach to compensate for the movement and then improve image quality. Recently, it was observed that the performance of image registration algorithms is highly affected by the anisotropic resolution of OCT images. In this study, the residual distortion (RD) was quantitively analyzed over different degrees of rotational movements and various lateral and axial pixel resolution ratio (R_L/R_A). The theoretical analysis confirmed that RD increases significantly with the rotation degree and R_L/R_A. An image resizing assisting registration (RAR) strategy was proposed for accurate registration. The performance of direct registration (DR) and RAR for retinal OCT and OCTA images were quantitatively compared. Experimental results confirmed that unnormalized R_L/R_A causes RD, RAR can effectively improve the performance of OCT and OCTA image registration and distortion compensation.

Iterative methods could provide high-quality image reconstruction for Fourier-domain optical coherence tomography (FD-OCT) by solving an inverse problem. Compared with the regular IFFT-based reconstruction, a more accurate estimation could be iteratively solved by integrating prior knowledge, however, it is often more time-consuming. To deal with the time problem, we proposed a fast iterative method for FD-OCT image reconstruction empowered by GPU acceleration. An iterative scheme is adopted, including a forward model and an inverse solver. Large-scale parallelism of OCT image reconstruction is performed on B-scans. We deployed the framework on Nvidia GeForce RTX 3090 graphic card that enables parallel processing. With the widely used toolkit Pytorch, the inverse problem of OCT image reconstruction is solved by the stochastic gradient descent (SGD) algorithm. To validate the effectiveness of the proposed method, we compare the computational time and image quality with other iterative approaches including ADMM, AR, and RFIAA method. The proposed method could provide a significant speed enhancement of 1,500 times with comparable image quality to that of ADMM reconstruction. The result indicates a potential for high-quality real-time volumetric OCT image reconstruction via iterative algorithms.

Corneal disease is the fifth leading cause of global blindless. Optical coherence tomography (OCT) for anterior imaging is extensively used due to its non-invasive and high-resolution volumetric imaging characteristics. Optical coherence microscopy (OCM) is a technical variation of OCT that can image the cornea with cellular resolution. Here, we demonstrate a visible-light OCM as a low-cost and easily reproducible system to visualize various corneal cellular structures such as epithelial cells, endothelial cells, keratocytes, and collagen bundles within stromal lamellae. The visible-light OCM was also used to study pressure changes in anterior segment human donor eyes. The system achieved an axial resolution of 12 μm in tissue over a 1.2 mm imaging depth, and a lateral resolution of 1.6 µm over a field of view of up to 750 μm × 750 μm.

Tumor heterogeneity is one of the greatest obstacles standing in the way of successful cancer therapy. Cancer in a single patient is not a single disease, but is a host of related diseases, all of which need to respond to a single treatment regimen. We have completed the first human clinical trial in esophageal cancer using dynamic-contrast OCT (DC-OCT) based on full-frame digital holography to assess the spatial heterogeneity of biopsy response to platinum-based chemotherapy. A deep twin neural network successfully identified biopsy sub-phenotypes in the dynamic tissue response that enabled accurate prediction of patient treatment success.

Optical coherence tomography (OCT) is a technique that is widely used to diagnose pathologies through morphological changes in tissue structure. OCT imaging of such structures based on the backscattered intensity provides qualitative images that are not quantitatively related to the tissue’s optical properties. Since certain pathologies affect optical parameters of tissues, such as the attenuation coefficient, quantification of the attenuation coefficient could be useful for medical diagnosis. For accurate quantisation of optical parameters robust depth resolved OCT models which are valid over a wide range of parameters are necessary.

Radiation therapy remains an essential component of cancer treatment, with nearly 50% of cancer patients receiving radiation therapy at some point during the course of their illness. Of those, the vast majority experience some form of acute radiation dermatitis (ARD) or radiation-induced skin injury. ARD results in significant discomfort, restriction of daily activities, overall decrease in the quality of life and even cessation of the necessary radiation therapy with detrimental survival effects. Unfortunately, research into the causes and possible management strategies for ARD is hindered by the lack of biomarkers for the quantitative assessment of the early changes associated with the condition. This study provides the basis to identify low grade ARD, using Optical Coherence Tomography (OCT) images with the extraction of conventional image intensity and novel features. Twenty-two patients were imaged twice each week until the end of their radiation treatment resulting in 1487 images. The severity of the cases was graded by an expert oncologist. The preliminary results of various machine learning (ML) classifiers have shown that an LDA based approach provided the best performance, separating normal skin from very early ARD, with an accuracy of 85%.

Jones matrix optical coherence tomography (JM-OCT) is a form of polarization-sensitive OCT (PS-OCT) that allows for the simultaneous and high-quality in vivo capture of multiple polarization-based imaging contrasts. Our system allows for the capture of high-sensitivity structural OCT, degree of polarization uniformity (DOPU), and birefringence images. Segmenting the epidermal-dermal junction is a topic of high interest in OCT and dermatology. While others have explored this with traditional OCT, no other groups have used this type of segmentation with JM-OCT. We believe that combining a reliable segmentation procedure with the robust and localized characterization provided by JM-OCT can help fully utilize the strengths of both techniques and allow for a better characterization of the skin layers. Here, we utilize JM-OCT to assess the skin properties of healthy volunteers. Using high-sensitivity OCT, we quantified the epidermal thickness of various locations in vivo and were able to segment the epidermis, dermis, and stratum corneum in thick skin. Polarization imaging is sensitive to specific structures in the skin, such as collagen and melanin, and we were able to quantify the depolarization, and birefringence caused by these structures in different skin layers. In thick skin, localized polarization results showed an average DOPU of 0.89 in the dermis compared to an average of 0.79 in the stratum corneum. However, in both thick and thin skin, DOPU was lower overall in the epidermis compared to the dermis, indicating that most observed depolarization occurs due to the structure of the stratum corneum. Birefringence was found to be higher in the dermis than the epidermis in both cases.

The healthy development of embryos depends on several critical biomechanical processes, such as neurulation and the formation of the cardiovascular system. Thus, understanding the structural modifications and changes in stiffness during development is important for understanding the etiology of various congenital diseases, such as anencephaly or spina bifida. In this work, we demonstrate the ability of reverberant optical coherence elastography (Rev-OCE) to map the biomechanical properties of various small animal embryos in high resolution in 3D completely noninvasively and without the need for any exogenous contrast agents. Rev-OCE measurements were performed in both murine and zebrafish embryos to showcase its capability to map the stiffness of commonly used small animal models of disease. The murine embryos were dissected from CD1 mice at gestational day 11, and the zebrafish embryos were isolated at 7 days post fertilization. Rev-OCE imaging was performed using a phase-sensitive optical coherence tomography (PhS-OCT) system, where the samples were placed on a glass window that was attached to a piezoelectric bender. The bender vibrated and generated randomly oriented shear waves in the samples, which were detected by the PhS-OCT system. In addition to holding the samples, the glass window enabled common path imaging for sub-nanometer levels of displacement sensitivity. The results show a clear spatial distribution of stiffness in the embryos. For example, the spinal region of the murine embryos was stiffer than other tissues, and in the zebrafish embryos, the head and swim bladder were stiffer. Embryonic elasticity could provide valuable insight into the critical embryonic developmental process and etiology of various congenital defects.

In neurosurgical tumor operations on the central nervous system, intraoperative haptic information often assists for discrimination between healthy and diseased tissue. Thus, it can provide the neurosurgeon with additional intraoperative source of information during resection, next to the visual information by the light microscope, fluorescent dyes and neuronavigation. One approach to obtain elastic and viscoelastic tissue characteristics non-subjectively is phase-sensitive optical coherence elastography (OCE), which is based on the principle of optical coherence tomography (OCT). While phase-sensitive OCE offers significantly higher displacement sensitivity inside a sample than commonly used intensity-based correlation methods, it requires a reliable algorithm to recover the phase signal, which is mathematically restricted in the -π to π range. This problem of phase wrapping is especially critical for inter-frame phase analysis since the time intervals between two referenced voxels is long. Here, we demonstrate a one-dimensional unwrapping algorithm capable of removing up to 4π-ambiguities between two frames in the complex phase data obtained from a 3.2 MHz-OCT system. The high sampling rate allows us to resolve large sample displacements induced by a 200 ms air pulse and acquires pixel-precise detail information. The deformation behavior of the tissue can be monitored over the entire acquisition time, offering various subsequent mechanical analysis procedures. The reliability of the algorithm and imaging concept was initially evaluated using different brain tumor mimicking phantoms. Additionally, results from human ex vivo brain tumor samples are presented and correlated with histological findings supporting the robustness of the algorithm.

Colorectal cancer (CRC) is one of the top causes of malignancy in both men and women. Although screening has significantly reduced CRC mortality, colonoscopy suffers from inadequate inspection and sampling of the tissue, a limitation that can be addressed by Optical Coherence Tomography (OCT). The use of fractal analysis, which has been shown to estimate the scatterer size from OCT data, could help improve the classification of colon polyps as compared to using morphological information alone. For this study, thirty polyps were imaged immediately post excision, histologically processed, and both the OCT and H&E images annotated by an expert. Multi-step segmentation was used to segment the crypt regions. Fractal analysis of those areas was employed to estimate the nuclear size and classify the polyps as normal or tubular adenoma. This process resulted in an accuracy of 81% (92% sensitivity, 40% specificity) as confirmed by histology. The poor specificity can be partially attributed to the small number (only 5) of normal polyps and, more importantly, to the confirmed presence of other histological features which might influence the fractal analysis. The proposed approach must be expanded to include more polyps and further enhanced to improve its specificity. However, these preliminary results provide evidence that this method has the potential to perform scatterer size estimation and tissue classification from en face images, thus, providing a robust approach for the improvement of the accuracy of endoscopic OCT and, in the future, the effectiveness of colonoscopy.

We present a multiple instance learning-based network, MIL-ResNet14, detecting biomarkers for diabetic retinopathy in a widefield optical coherence tomography angiography dataset with high accuracy, without the necessity of annotations other than the information of whether a scan stems from a diabetic patient or not. Previously introduced deep learning-based classifiers were able to support the detection of diabetic biomarkers in OCTA images, however, require expert labeling on a pixel-level, a labor-intensive and expensive process. We evaluated our proposed architecture against two proven-capable classifiers, ResNet14 and VGG16. The dataset we applied for this study was acquired with a MHz A-Scan rate widefield Swept Source-OCT device. We utilized a total of 352 en face images, displaying retinal vasculature over a field of view of 18 mm x 18 mm. MIL-ResNet14 outperformed both other networks with an F-score of 0.95, a precision of 0.909 and an Area Under the Curve of 0.973. In addition, we could show via saliency overlays of gradient-weighted class activation mappings onto the en face images, that MIL-ResNet14 pays special attention to clinically relevant biomarkers like ischemic areas and retinal vessel anomalies. This could therefore function as a vigorous diagnostic decision support tool for clinical ophthalmologic screenings.

Noise decreases image quality in optical coherence tomography (OCT) and can obscure important features in real-time visualizations. In this work, we show that a neural network can be applied to denoise volumetric OCT data for intra-surgical visualization in real-time. We adapt a self-supervised training approach, not requiring any paired data for training. Several optimizations and trade-offs in deployment are required, with which we achieved processing times of only few milliseconds. While still being limited by the real-time requirements, denoising in this scenario can enhance surface visibility, and therefore allow guidance for more precise intra-surgical maneuvers.

In frequency-domain optical coherence tomography (OCT) only half of the available depth range is used. This is due to the occurrence of complex conjugate (CC) ambiguity, which is an artifact resulting from the symmetry properties of the Fourier transform on real-valued spectrum that undermines the optimal sensitivity window. Current approaches require additional active or passive components, and increase systems complexity and cost. We present a novel deep-learning method for CC removal (CCR) based on a generative adversarial network (GAN). The model was trained to learn how to translate OCT scans with CC artifacts into full range images without the requirement of additional equipment or measurement. The data was collected from a phantom sample and human skin in vivo, using a swept source-OCT prototype. The GAN architecture adopted is based on the Pix2Pix model, where the discriminator is a PatchGAN and the generator is a U-net with skipped connections, and has been adapted for high resolution images of 864 × 1024 pixels. CCR-GAN receives as input the complete OCT signal, which consists of intensity and phase images. The findings and the evaluation metrics show that our model is able to effectively suppress CC artifact in OCT scans thereby providing a doubled imaging range. We demonstrated that our model is superior to prior approaches with respect to design complexity, imaging speed, and cost. CCR-GAN can be effectively used to suppress the CC mirror terms and generate full depth range in clinical imaging, that requires large ranging depth and high sensitivity.

Newts have a remarkable ability to regrow organs, providing key insights into the mechanisms of tissue regeneration. Lens regeneration in newts only initiates from the dorsal iris, and the underlying mechanism remains unknown. Understanding this process is critical for triggering non-competent adult tissues to support somatic cellular plasticity. Studies have focused on the difference in morphological and genetic variations between dorsal and ventral iris during the lens regeneration process using endpoint ex vivo tissue imaging and analysis, however, lens regeneration is a dynamic process. Therefore, this study aims to characterize the lens regeneration process in vivo with OCT and OCTA to non-invasively visualize the morphological variation of the anterior chamber and vasculature injury responses in the iris. Our results demonstrate that OCT is an ideal platform for in vivo monitoring lens regeneration in newts and provides a dynamic insight into this process.

Noninvasive cardiac control has stemmed from a need to overcome challenges that come from traditional electric implantable pacemakers, which can require surgery, cause infection and damage to vessels, and require battery replacements. Therefore, new methods are being developed to be able to control heart function noninvasively, specifically, using light. Previously, Drosophila have been used as a model for cardiac optogenetic studies, where the heart was able to be paced both slower and faster than its resting heart rate. This study looks at how reduced graphene oxide (rGO) can be used to increase the heart rate of yellow-white Drosophila pupa using light stimulation from 470 nm (blue light), 617 nm (red light), and 656 nm (near-infrared light). When injected into the heart tube of pupa, it forms aggregates along the heart wall and changes the membrane potential when light is shown, which leads to an increase in heart rate. Our study characterized the heart response to rGO stimulation, utilizing rGO’s broad absorption spectrum. Optical coherence microscopy (OCM) was used to image a cross-section of the heart tube over time, providing information about heart rate, rhythmicity, and morphology. This work is promising for use in both heart disease models, as rGO stimulation does not require prior genetic manipulation, and in larger animal models, where near-infrared light can be used to penetrate the heart when it lies deeper into tissue.

Ovarian tissue cryopreservation is used to frozen preserve ovary tissue for reimplantation, potentially restoring a cancer patient’s fertility after chemo and/or radiation treatment. The selection of ovary tissue containing many primordial and secondary follicles for reimplantation increases the probability of pregnancy, but it is a challenging task. In this work, we used spectral-domain OCT to evaluate the feasibility of non-invasively characterizing the morphology of ovary follicle development and age-related modifications in mice. The measured dimension and agerelated number of follicles presented a good agreement with corresponding histological images, demonstrating the potential to use OCT to evaluate ovary tissue for reimplantation.

Deep learning boosts the performance of automatic OCT segmentation, which is a prerequisite for standardized diagnostic and therapeutic procedures. However, training deep neural network requires laborious data labeling, and the trained models only work well on data from the same manufacturer, imaging protocol, and region of interest. Here we propose a novel learning method to reduce labeling costs. By labeling and training on a single image, we achieved segmentation accuracy comparable to that of a U-Net model trained on ~25 to 50 labeled images. This reduction in labeling costs could significantly improve the flexibility and generalization of deep-learning-based OCT segmentation.

The ability to detect the malignancy inside the tissue structure non-invasively have immense potential in the clinical application. In this work, a Bessel beam axicon probe based common-path optical coherence tomography system is demonstrated for detection of malignancy inside the human tissue. This probe is employed in this system having an axicon structure which is chemically etched inside the optical fiber end. This probe generates a quality Bessel beam owning a large depth-of-field, ~700µm and small central spot size. This probe effectively identifies the malignancy in the human colon tissue hence it could be a great tool as an endoscopic probe in future for either early-stage or during surgery diagnosis.

We propose a long-term stable model eye with three-layered retinal phantom. The layers are made of fluorosilicone which refractive index is 1.38 and includes fine particles of TiO₂ or polystyrene. The particle mixing amount is determined with respect to haze for each layer to achieve OCT images resemble to those of human retina. Stable liquid of fluorinated oil is filled in vitreous-mimic cavity. In addition, high-temperature durability test indicates that the model eye has high stability for more than six years. We have successfully obtained OCT images of the model eye, which are comparable to those of human eyes.

We demonstrate, to our knowledge for the first time, an integrated light source module that emits broadband amplified spontaneous emission (ASE) light from two superluminescent diodes (SLEDs) through a single-mode fiber output simultaneously on two orthogonal polarizations. The dual-polarization SLED source is realized on a free-space, temperature-stabilized, micro-optical bench and integrated in a 14-pin butterfly module. The broadband light output from the single-mode fiber has twice the output power of a single-SLED source and achieves a polarization extinction ratio (PER) of 0 dB when the relative power levels of both SLED sources are carefully balanced.

Mechanical signaling in vascular tissue can have major effects on remodeling outcomes and the viability of bypass grafts. When a vein is placed into an environment matching that of an artery, the vein begins to remodel to act like an artery. This change is dependent on mechanotransduction pathways that sense stress from the blood flow. To properly study these pathways, vessels need to be studied ex vivo to control the stress patterns vessels will experience within a patient. The mechanical properties of the vessel will then need to be analyzed at a cellular level to correlate the strain of the environment to the cell response. Optical coherence tomography (OCT) is able to capture b-scans of the entire vessel wall to observe changes at different lateral and axial positions. Multiple b-scans can be captured as the vessel experiences a pressure waveform mimicking physiological pressures and digital image correlation (DIC) can be performed to quantify the mechanical response of the tissue at each spot in the b-scan. A custom-built optical coherence tomography system was used to record images of a porcine carotid artery undergoing pressure changes to observe movements inside the vessel wall. DIC was performed to correlate the strain of the tissue to the experienced stress as a means of testing the system. This imaging method will provide valuable mechanical information as a vein is remodeled in a perfusion bioreactor.

In this study, we propose a B-scan-wise-multi-focus averaging method (B-MFA) to suppress the multiple scattering noise in optical coherence tomography. This method uses multiple B-scans with different focus positions. These B-scans were one-dimensionally computationally refocused and complex averaged. To verify the multiple scattering noise suppression ability of this method, we measured a phantom consisting of scattering and non-scattering layers. The results show that BMFA suppresses multiple scattering noise.

OCTSharp is a versatile open-source OCT software that aims to support real-time OCT imaging development in research labs. For high-speed imaging, OCT demands high-performance real-time data processing and visualization. However, hardware control and sophisticated memory management prevent agile prototyping. The proposed OCTSharp allows users to tailor OCT for specific purposes in a short development cycle. This software is based on managed C# environments with accessible hardware control, minimal memory management, and GPU support. We demonstrate that OCT software based on C# is highly efficient and can satisfy most research-level OCT applications.

Optical coherence tomography (OCT) has become increasingly essential in assisting the treatment of coronary artery disease (CAD). Image-guided solutions such as Percutaneous Coronary Intervention (PCI) are extensively used during the treatment of CAD. However, unidentified calcified regions within a narrowed artery could impair the outcome of the PCI. Prior to treatments, object detection of the diseased regions is paramount to automatically procure accurate readings on calcifications within the artery. Though deep learning-based object detection methods have been explored in a variety of applications, the quality of predictions can be negatively impacted by overconfident deep learning models, which is not desirable in safety-critical scenarios. In this work, we adopt an object detection model to rapidly draw the calcified region from coronary OCT images using bounding box. We evaluate the uncertainty of predictions based on the expected calibration errors, thus assessing the certainty level of detection results. The calibrated confidence of prediction results in a confidence error of approximately 0.13, suggesting that the confidence calibration on calcification detection could provide a more trustworthy result, which indicates a great potential to assist clinical evaluation of treating the CAD during the imaging-guided procedure.

Due to its superior imaging performance Swept Source Optical Coherent Tomography (SS-OCT) has become an established 3D imaging methodology. One of the key elements of this technique is the swept source as its tuning range and tuning speed will define the axial resolution and the time required to acquire an A-scan. This work presents the characterization of the performance in SS-OCT of an electrically pumped Microelectromechanical Movable Mirror Vertical Cavity Surface Emitting Laser (MEMS-VCSEL) in the range from 1540-1600nm. To investigate the tuning performance of the MEMS-VCSEL its output signal is amplified with and Erbium doped (Er⁺) fiber amplifier connected to an OCT system where the channelled spectrum is processed by using a Complex Master Slave (CMS) method that evaluates the nonlinearity in tuning in both forwards and backwards tuning for tuning frequencies of 10, 50 and 100 Hz. The results obtained show that the linearity of the device increases as the tuning frequency does and it has a sensitivity roll-off at 6dB of 12.65 mm which is equivalent to an instantaneous linewidth of 85pm.

We developed a three-dimensional motion tracking method based on circular scans with optical coherence tomography. For transverse motion, the detectable speed ranges from millimeters to centimeters per second, while for axial motion, it ranges from micrometers to millimeters per second for axial motion. This method provides fast and high-precision measurements of the sample motion in both magnitude and direction, which will provide active motion compensation via feedback control for in vivo microscopic and macroscopic imaging applications in the future.