This PDF file contains the front matter associated with SPIE Proceedings Volume 12632, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Three-dimensional (3D) cellular-resolution imaging of the living human retina over a large field of view would bring a great impact in clinical ophthalmology, potentially finding new biomarkers for early diagnosis and improving the pathophysiological understanding of ocular diseases. While hardware-based and computational Adaptive Optics (AO) Optical Coherence Tomography (OCT) have been developed to achieve cellular-resolution retinal imaging, these approaches support limited 3D imaging fields and their high cost, and their intrinsic hardware complexity limit their practical utility. Here, we demonstrate 3D depth-invariant cellular-resolution imaging of the living human retina over a 3-mm × 3-mm field of view using the intrinsically phase-stable multi-MHz retinal swept-source OCT and tailored computational defocus and aberration correction methods. Single-acquisition imaging of photoreceptor cells, retinal nerve fiber layer, and retinal capillaries is presented across unprecedented imaging fields. By providing wide-field 3D cellular-resolution imaging in the human retina using a standard point-scan architecture routinely used in the clinic, this platform proposes a strategy for expanded utilization of high-resolution retinal imaging in both research and clinical settings.

We developed and applied Spatio-Temporal Optical Coherence Tomography (STOC-T), which supported by computational aberration correction enables high resolution imaging of the human and mouse retina in vivo.

We present our progress on image-guided (sensor-less) adaptive optics for multi-modal imaging of retinal tissue using high numerical aperture OCT and confocal microscopy using a custom developed instrument. Images of ex vivo tissues are compared to data acquired in vivo.

Our research investigates retinal pigmentary abnormalities in Retinitis Pigmentosa (RP) patients using ultra-wide-field high-speed Polarization Diversity Optical Coherence Tomography (PD-OCT) in a clinical setting. To account for the retinal curvature in the wide field of view, adaptive kernel-based spatial averaging is employed for Degree-of-Polarization-Uniformity (DOPU) contrast formation with two complex OCT signals from two orthogonal polarization channels. 20 patients diagnosed with RP were recruited for this study and imaged with PD-OCT. Then, the melanin distribution images from PD-OCT were compared to standard multimodal imaging techniques, including intensity-based OCT, fundus photography, and short-wavelength fundus autofluorescence images. Wide-field PD-OCT imaging technique presented in this study was capable of precisely assessing melanin-related changes in RP over a large field of view and monitoring the disease progression. As a next step, we are investigating the correlation of specific genetic mutations in RP patients with specific clinical presentations and disease progression rates as assessed by the quantitative measurements in PD-OCT. The clinical findings will be presented during the conference.

The unmet medical need of continuously monitoring retinal disease progression asks for an affordable and easy to use medical device that can be used multiple times per week at the patient’s home. A retinal monitor system has been designed for home use, has been built, and tested in a clinical study. The retinal monitor system consists of a handheld device operated by the patient, a tablet with an application, and cloud software. The retinal monitor system has been optimized for low production cost and ease of use for elderly patients while a minimum required performance has been assured to detect changes of retinal thickness and the presence of fluid. Component costs are optimized by relying on the wavelength-tuning capabilities of a VCSEL light source. The small form factor, the lightweight design and an auto-capture functionality enable patients to operate the retinal monitor on their own. The limited performance of low-cost components is compensated by sophisticated signal processing including a deep neural network. Clinical data has been acquired on 20 healthy and 50 diseased eyes to develop the algorithm and estimate the device performance. The clinical results indicate a 95% sensitivity and 95% specificity to detect a change of ±25 μm. Moreover, presence of fluid has been detected with a true positive rate of 97% and a true negative rate of 92%.

Attenuation coefficient imaging stands to enhance the value of Optical Coherence Tomography (OCT) in clinical assessment of dysplasia. We present results combining novel signal processing and hardware strategies to more accurately acquire and analyze scattering properties in tissue to extract clinically meaningful morphological information.

We have developed a multifunctional catheter-based OCT system, which provides architecture and birefringence information of biological tissue and allows volumetric imaging of the luminal part of the cervix. Preliminary imaging results of the in vivo human buccal mucosa and tongue were shown to validate the capabilities of volumetric imaging in the developed multifunctional OCT system, and further obtained the birefringence information by analyzing the polarization information of the OCT signal to implement the multifunctional OCT imaging.

Asthma is an inflammatory disease, causing thickening of the Airway Smooth Muscle (ASM). No current method exists to directly measure ASM within a living patient. Endoscopic Polarization Sensitive Optical Coherence Tomography (PS-OCT) might enable quantification of ASM mass in vivo, by assessing tissue birefringence. We performed in vivo PS-OCT on severe asthma patients and healthy volunteers, with an in-house built distal scanning catheter (1.35 mm), to circumferentially scan the airways at 52 fps B-scan rate. We provided the first comparison of in vivo PS-OCT images between asthma and healthy subjects and demonstrated the ability of PS-OCT to assess ASM content.

We present an ultrahigh-speed Swept Source Optical Coherence Tomography (SS-OCT) system that allows a volume rate of 400 Hz paired with a Time Domain (TD) subsystem. For the SS-OCT, a 40 MHz swept source is used, while for the TD-OCT, a broadband source. Both systems employ a scanning system that consists of a KTN scanner paired with a galvoscanner. The KTN crystal scans the beam laterally at 100 kHz. This allows B-scan OCT repetition rate, while with the galvoscanner 200 lines are obtained at 400 Hz in the en-face display of both SS-OCT and TD-OCT systems.

Barrett’s Esophagus (BE) is a common pre-cursor condition to Esophageal Adenocarcinoma (EAC); the monitoring of which can facilitate the detection of dysplastic tissue, and the treatment of subsequent early stage EAC. Early detection of EAC improves survival rates significantly. Optical Coherence Tomography is a low coherence interferometric technique which produces depth scans of tissues. OCT provides morphological information, but lacks in specificity, and so can be combined with Near Infrared Fluorescence imaging, to also retrieve molecular information. Fluorescently labelled monoclonal antibodies can be administered in order to label specific tissues, which can then be imaged using this OCT-NIRF technique. Fluorescently labelled bevacizumab combined with OCT-NIRF imaging will highlight inflamed, dysplastic and pre-/cancerous tissues, such as BE tissue. Here, silicon elastomer phantoms are used to quantify the fluorescence intensity signal detected from a dilution of fluorescent bevacizumab: the fluorescent signal intensity is correlated as a function of fluorophore depth and concentration, and μ′_𝑠value of the phantom material.

In this summary, a new, fully akinetic FDML-like or so-called dual resonance sweeping regime for swept source optical coherence tomography, SS-OCT, at 1060 nm is demonstrated. A chirped fiber Bragg grating is used to provide sufficient dispersion in the laser cavity and a fiber intensity modulator is employed to modulate the optical field in the fiber cavity. A tuning range of 40 nm for sweep frequency of ≈ 1.7 MHz is obtained. Similarities in the operation of the dual resonance regime with a conventional dispersion tuned swept source and the FDML concept are included.

In this report, a novel calibration method is introduced, which can be used in camera-based Optical Coherence Tomography (OCT) instruments employing several spectrometers. To ensure that all spectrometers are calibrated, i.e. they sense the same spectral range and the distribution of the optical frequencies across the pixels of the cameras is the same, a hybrid method was used involving (i) a hardware procedure for an initial estimation of the edges of the spectra and (ii) a numerical Monte-Carlo based technique. The utility of such a procedure is demonstrated in an OCT system using a Balance-Detection (BD) scheme. The OCT system employs a single transmission diffraction grating and is driven by a supercontinuum source operating in the visible spectral range. Spectral alignment is paramount in producing high-sensitivity images free of artefacts. To ensure correct calibration, and speed up the calibration procedure, the Master-Slave (MS) technique of generating axial reflectivity profiles is employed. Preliminary results show an improvement of the signal of ~ 3dB and a mitigation of the background noise of over 5 dB.

A combined LC-OCT and dermoscopy system is presented. The LC-OCT modality allows to obtain real-time in-depth cross-sectional and 3D images with an isotropic cellular resolution, providing a comprehensive view of the in-depth tridimensional morphology of the skin at a resolution similar to histology. The dermoscopy modality provides color images of the surface of the skin, serving as a guiding tool for LC-OCT, and complementing the in-depth cellular information of LC-OCT with a high-resolution view of the skin surface. The system has been applied to in vivo imaging of various skin lesions, including carcinomas and melanomas.

The collagen layer of the human Tympanic Membrane (TM), which is essential for sound conduction and hearing, can be assessed in vivo by using endoscopic Polarization-Sensitive Optical Coherence Tomography (PS-OCT), as we have shown recently. Since the resolution of the utilized system was limited, an ex vivo validation of the structural information is presented here. By comparing higher resolution PS-OCT images of a temporal bone specimen and Polarized Light Microscopy (PLM) of histological slices from that TM with picrosirius red staining, the microstructure is investigated.

Type 2 Diabetes Mellitus (T2DM) is increasing in prevalence and its complications are potentially fatal. Recent studies suggest that long-term complications of T2DM include alterations of the bone, evident by a high coexistence rate of diabetes mellitus with both osteoporosis and different fracture types. Current measurements of fracture risk are based on Bone Mineral Density (BMD) measured via Dual-energy X-ray Absorptiometry (DXA); however, this method does not measure bone quality and often underestimates fracture risk in T2DM. Optical Coherence Tomography (OCT) holds the promise of early detection of diabetic bone microarchitectural alteration and serves as a possible non-ionizing alternative to DXA. The aim of this study is to evaluate the viability of using OCT-derived attenuation coefficients as a method for differentiating between healthy and diabetic bones in a diagnostic process. A TALLYHO/JngJ mouse model of diabetes was used and compared to a healthy control SWR/J; the differences in bone structure and quality of the TALLYHO/JngJ model compared with SWR/J is well documented in the literature. OCT cross-sectional images of four ex-vivo mouse femurs, two healthy and two T2DM, were used to calculate attenuation coefficients. Coefficients were calculated for the anterior side and the posterior side of the femurs. The posterior side was used as a control for the anterior side of the same femur sample. The attenuation-based comparison between healthy and diabetic bones shows that it is possible to differentiate between healthy and diabetic bones (p = 0.002). No significant difference in attenuation between the anterior and posterior side (p = 0.543, T2DM and p =0.055, healthy) was found. These preliminary results indicate that OCT-derived attenuation coefficients have the potential to differentiate between healthy and diabetic bones in a mouse model of T2DM.

Endoscopic Optical Coherence Tomography (OCT) enables the assessment of the eardrum and the middle ear in vivo. However, revealing the ossicles is often limited due to shadowing effects of preceding structures and the 3D impression is difficult to interpret. To compare the identified middle ear structures, OCT and cone-beam CT of a patient were spatially aligned and showed a good agreement in locating malleus and the promontory wall. As CT imaging uses ionizing radiation and is thus limited in application, we furthermore provide a concept how radiology can be utilized as a priori knowledge for OCT imaging. Therefore, a statistical shape model derived from μCT data of temporal bone specimens was fitted to in vivo OCT measurements, potentially providing a real-time augmentation of endoscopic OCT for middle ear diagnostics in the future.

Small defects in dental crowns due to the manufacturing or physiological/non-physiological stress in patients’ mouth can result in failure of restorations and sometimes even lead to the extraction of the tooth itself. If those microcracks can reliably be detected, defective crowns can be sorted out or be repaired in case of fatigue damage. Currently there is no non-destructive method to visualize microcracks within Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM)-materials, neither for dentists nor manufacturers. Therefore, eight different monolithic CAD/CAM-materials were inspected by different Optical Coherence Tomography (OCT) systems before and after mouth-motion-simulation. All OCT devices were suitable to visualize microcracks in the crowns. However, differences regarding parameters and CAD/CAM-materials were detected.

Due to the presence of highly scattered inclusions or impurities on the surface or inside of the tooth, resulting in loss of Optical Coherence Tomography (OCT) signal under the aforementioned defects including image-accurate assessment teeth. In this study, we developed a multi-view multiplexing algorithm based on the nearest point repeat (ICP) algorithm to reconstruct the missing information. The use of a biaxial angle stage allows for multi-view images to be obtained at varying degrees of control. The result of our proposed method is that it is possible to improve the Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR) of dental OCT images.

The development of functional retinal imaging is of great interest to clinical and experimental ophthalmology because it should improve current clinical practice that relies on a simple evaluation of disease-related changes in retinal morphology. In this presentation, we will review our recent progress in the measurements and interpretation of Optoretinograms (ORG). The ORG comprises light-dependent changes in photoreceptor outer segment length and scattering measured in vivo with submicrometer-resolution by Optical Coherence Tomography (OCT). Our recent data confirm that the mechanisms underlying “slow” ORG response is that extreme phototransduction increases osmotic pressure in the outer segment, driving water entry and swelling to restore osmotic balance. Water movement between different retinal layers was quantified by OCT measurements, and analysis of retinal layer thickness dynamics provided estimates of the water permeability of key barriers between the Choriocapillaris (CC) and photoreceptors, viz., of the CC cell membrane, Bruch’s Membrane (BrM), the RPE layer, and the rod plasma membrane. A model proposed to link the changes in refractive index caused by the osmotically driven water movement between the CC lumen and the outer segment during the ORG predicts the observed BrM scattering changes. Overall, the results and modeling provide new insights into critical water barriers of the posterior eye and an experimental and theoretical toolkit for measuring their permeabilities.

We use Spatio-Temporal Optical Coherence Tomography (STOC-T) to record flicker ORG signals. The chirped frequency stimulus (5 Hz to 45 Hz) provides a more convenient way of measuring photoreceptors' frequency characteristics. Our method detected significant differences in response amplitudes in two measured subjects when comparing responses to different stimulus amplitudes as well as when comparing responses to rectangular and sinusoidal stimulation.

The proposed preclinical study investigates pathological characteristics of retinal diseases such as Age-related Macular Degeneration (AMD) with transgenic small animal models using a multi-modal functional small animal retinal imaging system. For characterizing the animal models, we visualize the melanin concentration, lipofuscin accumulation, and choriocapillaris using a single imaging system. The system implements Polarization-Sensitive Optical Coherence Tomography (PS-OCT), fluorescence Scanning Laser Ophthalmoscope (fSLO), and Sensorless Adaptive Optics (SAO) for the visualizations of pathological features. As preliminary data, we acquired three different mice models and visualized the outer retinal thickness and melanin concentration. The newly developing system is expected to provide multilateral perspectives for further studies in AMD, enabling vision scientists to investigate the correlations between melanin, lipofuscin, and choriocapillaris for the root cause of AMD.

We present a novel ultrafast imaging system using Spatio-Temporal Optical Coherence Tomography (STOC-T), capable of acquiring structural images of a mouse retina at a volumetric rate of 112 Hz. A calibrated fundus camera and white-light illumination aid the alignment of the mouse and the adjustment of the focal plane in the mouse retina for the STOC-T image. We extract pulsatile blood flow frequency and other hemodynamic parameters from multiple retinal and choroidal vessels from structural-only OCT images, highlighting the prospects of STOC-T for monitoring retinal hemodynamics in a simple way.

Recently, there has been vast interest in probing photoreceptor dynamics using optical coherence tomography (OCT). Most successful demonstrations implemented adaptive optics or digital adaptive optics to resolve individual cones or rods in human subjects. Here we use phase information to trace the photoreceptor response in rodents using an ultrahigh-resolution, phase-sensitive, spectral-domain OCT. Brown Norway rats (six to 14 weeks) were sedated using a ketamine and xylazine cocktail. Repeated scans were registered by a phase-restoring subpixel motion correction algorithm to isolate the bulk motion, and two hyperreflective bands (inner segment/outer segment junction – IS/OS; outer segment tip + retinal pigment epithelium + Bruch's membrane) were segmented automatically. As a result, two types of nanoscale signals (biphasic Type-I and monophasic Type-II) were detected with a clear separation in depth. We tested the repeatability, scotopic stimulus strength dependency, and photopic background intensity dependency. Besides, we demonstrated enface mapping of the ORG signals in a wide field of 20°, analogous to the multifocal electroretinogram but with a much higher resolution, revealing the spatial distribution of the outer retina function. This method could be extended to study animal models with photoreceptor degeneration and clinical studies to investigate early photoreceptor dysfunction with high spatiotemporal resolution.

Corneal diseases are the fifth leading cause of visual loss globally. Current clinical imaging instruments such as In Vivo Confocal Microscopy (IVCM) offer high lateral resolution to observe cellular structures but lack large field of view and volumetric imaging capability and require high operator skill to focus and align. To overcome these limitations, we have developed blue (450 nm) and green (510 nm) light Optical Coherence Microscopy (OCM) to image cellular structures. Imaging was demonstrated in ex vivo samples including human donor eyes. The OCM systems were based on a spectral-domain optical coherence tomography engine and achieved 750 μm × 750 µm field of view, 1.2 mm imaging depth, and 1.6 μm lateral resolution. Epithelial cells, endothelial cells, and keratocytes of ex vivo rabbit cornea were visualized. Additionally, collagen fibers were observed in stromal lamellae with striated patterns. En face and cross-sectional images of trabecular meshwork and Schlemm’s canal in a donor human eye wedge were observed at various trans-meshwork pressures controlled by cannulation of the canal. Microbes such as filamentous fungi and bacteria were observed.

The trend towards homecare and point-of-care devices in medical care triggers the need for more compact and economic medical diagnostic technology. With this goal, we developed a flexible low-cost long-range SS-OCT capable of imaging the human eye from anterior to posterior segment, based on a single-mode tunable VCSEL at 850 nm. The system runs at A-scan rates of 2-25kHz with a measured maximum sensitivity of 97dB. In this work, we present in-vivo results of full eye imaging with an imaging range of 5 cm including both anterior and posterior segment B-scans.

Photorefractive Keratectomy (PRK) is a widely used laser-assisted refractive surgical technique. While generally safe, in some cases it leads to subepithelial inflammation or fibrosis. We here present a robust, machine learning based algorithm for the detection of fibrosis based on Spectral Domain Optical Coherence Tomography (SD-OCT) images recorded in vivo on standard clinical devices. The images first undergo a treatment by a previously developed algorithm for standardisation. The analysis of the pre-treated images allow the extraction of quantitative parameters characterizing the transparency of human corneas. We here propose an extension of this work. Our model is based on 9 morphological quantifiers of the corneal epithelium and in particular of Bowman's layer. In a first step it is trained on SD-OCT images of corneas presenting Fuchs dystrophy, which causes similar symptoms of fibrosis. We trained a Random Forest model for the classification of corneas into "healthy" and "pathological" classes resulting in a classification accuracy (or success rate) of 97%. The transfer of this same model to images from patients who have undergone Photorefractive Keratectomy (PRK) surgery shows that the model output for probability of healthy classification provides a quantified indicator of corneal healing in the post-operative follow-up. The sensitivity of this probability was studied using repeatability data. We could therefore demonstrate the ability of artificial intelligence to detect sub-epithelial scars identified by clinicians as the origin of post-operative visual haze.

We describe an automated algorithm allowing extraction of quantitative corneal transparency parameters with clinical Spectral-Domain Optical Coherence Tomography (SD-OCT). Our algorithm employs a novel pre-processing procedure to standardize SD-OCT image analysis and to numerically correct common instrumental artifacts before extracting mean intensity stromal-depth (z) profiles over a 6-mm-wide corneal area. The z-profiles are analyzed using our previously developed objective method deriving quantitative transparency parameters which are directly related to the physics of light propagation in tissues. Tissular heterogeneity is quantified by the Birge ratio, B_r; for homogeneous tissues (i.e., B_r~1), the photon mean-free path (ls) may be determined. Images of 83 normal corneas (ages 22–50 years) from a standard SD-OCT device (RTVue-XR Avanti, Optovue Inc.) were processed to establish a normative dataset of transparency values. After confirming stromal homogeneity (B_r⪅10), we measured a median ls of 570 μm (interdecile range: 270–2400 μm). Considering corneal thicknesses, this may be translated into a median fraction of transmitted (coherent) light Tcoh(stroma) of 51% (interdecile range: 22–83%). Excluding images with central saturation artifact raised our median Tcoh(stroma) to 73% (inter-decile range: 34–84%). These transparency values are slightly lower than previously reported, which we attribute to the detection configuration of SD-OCT with a relatively small and selective acceptance angle. No statistically significant correlation between transparency and age or thickness was found. Our algorithm provides robust and quantitative measurements of corneal transparency from standard SD-OCT images with sufficient quality and addresses the demand for such an objective means in the clinical setting.

A new formulation of Optical Coherence Tomography (OCT) is presented. This formulation can represent a meaningful OCT image and speckles as two independent mathematical entities. In addition, by using the same formulation strategy, a new imaging modality to generate a spatially differential image, similar to differential interferometric contrast microscopy is demonstrated.

Realistic modelling of image formation in optical coherence tomography, which models light propagation in the sample using Maxwell’s equations, is useful for applications such as training researchers and clinicians, image interpretation and technique development. Such models, however, require specialized knowledge of numerical techniques for solving Maxwell’s equations, and for modelling optical systems. Here I present a freely available, open-source package, aimed at making such simulations accessible to researchers throughout the optical coherence tomography community. Time Domain Maxwell Solver (TDMS) is based on the Finite Difference Time Domain (FDTD) and Pseudo Spectral Time Domain (PSTD) methods and includes functionality required to model optical systems typically found in OCT systems. TDMS includes several use case examples aimed at making it easy for users with limited background in simulation to use the package.

A neural network is proposed as a much better performing alternative to Fourier transformation. It processes raw OCT spectra into A-scans with twice better nominal axial resolution which remains intact at all depths even for an uncalibrated spectrometer and uncompensated chromatic dispersion.

Quantitative OCT measurements of optical parameters such as the attenuation coefficient could allow for better differentiation between healthy and diseased tissues. To investigate relationship between the attenuation coefficient and OCT signal we developed a Monte Carlo (MC) simulation method for OCT measurements that takes into account the confocal function. To validate the MC model simulations were compared to OCT measurements on phantoms. Both the A-lines, and attenuation coefficients extracted from the A-lines based on a singly scattered model, matched well between the simulated and experimentally measured data.

Modern conception of Optical Coherence Tomography (OCT) measurement covers a wide range of measurement acts from photo-detection to Artificial-Intelligence (AI) based diagnosis. Here the measurement targets may include the structure, optical properties, tissue (by image processing and segmentation), and disease (by computer-aided diagnosis). Despite recent rapid expansion of the measurement targets, there is not theoretical (speculative) model to comprehend such wide spectrum of the measurement acts. Here we present a new speculative (theoretical) modeling of optical measurement, so-called “epistemological metrology model.” We use this model to critically understand several modern extensions of Optical Coherence Tomography (OCT), such as computer-aided diagnosis, Degree-of-Polarization-Uniformity (DOPU) imaging, and Attenuation-Coefficient (AC) imaging.

Line-field Confocal Optical Coherence Tomography (LC-OCT) is a non-invasive optical technique for imaging the skin in vivo in depth and at high resolution. Confocal Raman Microspectroscopy (CRM) is a label-free technique that provides point-wise information on the molecular content of the analyzed sample. We present the development of a prototype platform allowing the co-localized acquisition of LC-OCT images and Raman spectra on ex vivo skin samples with an accuracy of ± 20 μm. We present results obtained on healthy skin as well as preliminary results obtained on a basal cell carcinoma surgery, aiming at identifying molecular tumor markers.

In this work, intensity and polarization OCT were applied, simultaneously, to alpha-sarcoglycan deficit mice models, and a new visualization technique was implemented, based on encoding the attenuation and birefringence values in the HSV color space. Our samples consisted of 14 ex-vivo mice quadriceps at different disease stages (one, three, and six-month-old mice) and four healthy ones for reference. The healthy muscles present a different birefringence distribution to the dystrophic ones, while attenuation values for both kinds of samples lay in the same range. Nevertheless, the attenuation provides an increase in contrast and textural features that are not visible by only using birefringence, while the latter, encoded in the H coordinate, helps to easily identify damage inside the samples by color.

Although the knowledge about Sudden Cardiac Death (SCD) and its risk factors and treatment is continuously growing, it still remains the most likely reason of mortality in western countries. In general, the short timespan between witnessed symptoms and sudden death caused by cardiovascular disease is about one hour or, if no symptoms are observed, 24 hours. The preliminary occurring Sudden Cardiac Arrest (SCA) bases in approximately 70% of all SCD cases on Coronary Heart Diseases (CHD) provoking Myocardial Infarctions (MI) by atherosclerotic plaque on myocardial relevant arteries. Consequently, the restricted blood flow reduces the oxygen density triggering the mechanism of fibrotic scarring, in which connective tissue replaces the functional muscle tissue. This unexcitable collagenous scar tissue alters the myocardial conductivity. Untreated, arrhythmias, in particular ventricular fibrillation (VF), can be initiated being responsible for 50% of total SCD3,4. During VF ventricular muscles twitches randomly rather than contracting ending up with an interrupted pump activity. Recent developments show that the correction of cardiac conductivity by using Catheter Ablation (CA) can decrease the risk of VF and, consequently, SCD. An Electrophysiology Study (EPS) offers the electric potential map of the myocardium and indicates abnormal electrical circuits interrupting the propagation of electrical impulses. These causative fibrotic areas are terminated through heating induced by catheter-based electrodes with alternating current in the radiofrequency range. Low resolution aggravates a precise differentiation between affected and physiological myocardial tissue. In addition, applied to muscle tissue CA has also the ability to cause fibrotic scarring explaining the relation between unprecise guidance of CA and a higher probability of recurrences. Promising imaging modalities to increase the therapeutic success are advanced techniques such as Second Harmonic Generation (SHG) microscopy and Optical Coherence Tomography (OCT) for more sensitive diagnostics. SHG imaging can reveal density and individual fibril morphology of collagen. Classification into different stages of fibrillogenesis can be performed allowing allocation of examined cardiac tissue into non-infarcted, pharmacological treated and untreated. In contrast, OCT provides real-time three-dimensional imaging of tissue morphology. Switching from structural to spectroscopic investigation, Raman excitation offers the unique molecular fingerprint and, therefore, the conclusive evidence of molecular changes in point-scan acquisition. Accordingly, combining OCT, SHG microscopy and Raman spectroscopy in one setup with a shared sample arm and a common objective facilitates to benefit from the individual advantages of each modality.

Laser Speckle Contrast Imaging (LSCI) is an optical technique for noninvasive assessment of microcirculatory blood flow. LSCI has a broad application in medicine including dermatology. Since laser speckles are the basis for this imaging modality, any external motions during a measurement from both patient and operator affect the blood flow images. This challenge is called Motion Artefacts (MA). Here, we propose a complete procedure for analysis of speckles, that is, pre-segmentation, segmentation, motion detection, spatial alignment, perfusion map calculation and MA suppression. The Handheld Perfusion Imager (HAPI) operated in both handheld and mounted schemes, has been used for measurements on 14 psoriasis subjects. The advantage of HAPI is use of a single monochromatic camera for both speckle imaging and motion detection. We make use of the black marker dots (made by the clinical investigator to determine visual psoriasis lesion boundary) for calculation of two-dimensional displacements of HAPI during each measurement (i.e. on-surface displacements). These on-surface displacements are integrated to translate each speckle image back to the initial position at the start of the measurement (i.e. spatial alignment). Furthermore, in handheld measurements, MA corrected blood flow maps (also called perfusion maps) are formed by extrapolation of a linear fit from local perfusion versus detected speed to the zero speed, that is, a value ideally always lower than the local mean perfusion. We show that our MA suppression technique makes handheld perfusion maps more similar to the associated mounted perfusion maps in term image histograms and mean values.

Quantitative Micro-Elastography (QME), an emerging compression optical coherence elastography technique, is used to measure the mechanical properties of tissue on the microscale. As QME requires contact between the loading plate and the sample, knowledge of the boundary conditions at the contact surface, including friction, is required to accurately calculate elasticity. In previous implementations of QME, a lubricant is applied at the contact surfaces, and it is assumed that this results in negligible friction. In this work, for the first time, we demonstrate that experimental factors including the application method and viscosity of the lubricant, as well as the mechanical contrast between the compliant layer and the sample affect friction and, therefore, the accuracy of QME. For instance, in the absence of appropriate lubrication, errors as large as 92% were observed, while the development of an optimized lubrication protocol provided accurate elasticity measurements for a wide range of samples elasticity (from 3 kPa to 130 kPa) to within 10% error.

Optical coherence elastography represents mechanical characteristics of biological tissue in so-called mechanical contrast maps. In addition to the standard intensity image, the contrast map illustrates numerous mechanical tissue features that would otherwise be undetectable. This is of great interest as abnormal physiological changes influence the mechanical behavior of the tissue. We demonstrate an advanced mechanical contrast approach based on the phase signal of our 3.2 MHz optical coherence tomography system. The robustness and performance of this contrast approach is evaluated and discussed based on preliminary results.

We present an optical imaging system, termed Spatio-Temporal Optical Coherence Tomography, for high-resolution and fast in vivo imaging of chorioretinal complex. The system utilizes a fast camera and a swept laser source for fast volumetric data acquisition. A multimode fiber is used to break the spatial coherence of the laser that reduces the crosstalk noise in the OCT images. We choose the fiber parameters such that it gives the most optimal images in terms of signal strength, resolution and crosstalk reduction. We also test combinations of the fiber with other optomechanical devices in the attempt to further improve the images.

The laser nerve stimulation technique is an emerging stimulation method that utilizes some of the advantages of laser-tissue interaction. However, a narrow temperature range (41 °C – 48 °C) for successful, reliable, and safe laser nerve stimulation remains challenging for the method. This preliminary study investigates the depth-resolved thermal measurement performance of the system, comprising ⪆22 MHz Stretched-Pulse Mode-Locked (SPML) laser and a 1505 nm laser for laser nerve stimulation. Providing the OCT signal in M mode, the system successfully measured the change in fringe amplitude as a function of temperature increases in a phantom model.

Optical Coherence Tomography (OCT) is a well-established modality for structural and functional imaging of the biological samples. Conventional scanning OCT combines the low temporal coherence with confocal gating to reject multiply scattered light. However, OCT uses a spatially coherent light source, and thus, is susceptible to speckle noise, which reduces the transverse resolution. We use dynamic light scattering to improve the transverse resolution. The dynamic scattering particles induce speckles, that change over time due to particle displacement. By incoherently averaging OCT images acquired under different particle distributions, we effectively suppress the spatial coherence and improve transverse image resolution.

Multicellular spheroids are a powerful model to study biochemical and biophysical interactions between cancer cells during growth and progression. However, little is known about how the biomechanics of the three-dimensional (3-D) microenvironment control cancer cell behaviors due to the lack of enabling technologies that can measure 3-D subcellular-scale elasticity and co-register it with the morphology and function of cells in a 3-D microenvironment. Here, we propose a multimodal imaging system that integrates an optical coherence microscopy-based subcellular mechano-microscopy system with a multi-channel confocal fluorescence microscopy system. Using this multimodal imaging system, we scan non-metastatic MCF7 breast cancer cell spheroids encapsulated in gelatin methacryloyl (GelMA) hydrogels and co-register 3-D intra-spheroid elasticity with subcellular structures, such as nuclei and cell membranes.

We demonstrate label-free dynamic optical coherence tomography-based evaluation of tumor spheroids' response to multiple anti-cancer drugs based on different mechanisms. The study involved dynamic imaging of human breast cancer (MCF-7) spheroids treated with tamoxifen citrate (TAM), Paclitaxel (PTX), and doxorubicin (DOX). In addition, fluorescence (FLUO) imaging was performed as a reference. The D-OCT imaging is performed using a custom-built OCT device with a repeated raster scan protocol. Two algorithms, including Logarithmic Intensity Variance (LIV) and late OCT Correlation Decay Speed (OCDSl) were used to visualize the tissue dynamics. The D-OCT visualized the drug type-dependent morphological and tissue-activity response patterns of the tumor spheroid. The different response patterns are clearly explained by the mechanisms of the drugs. The presented results suggest that D-OCT can be a useful tool for anti-cancer drug testing.

The most successful methods for speckle reduction in Optical Coherence Tomography (OCT) are based on deformation of the wavefront used in scanning. Here, a simple method is presented where the wavefront is distorted by lateral translation of the lens between the 2D galvo-scanner and sample. The report demonstrates that the method can be implemented with a small piezoelectric transducer. Up to 33% improvement in Speckle Contrast Ratio (SCR) of B-scan OCT images is demonstrated.

We demonstrate the label-free intra-tissue activity imaging of human induced pluripotent stem cell (hiPSC)-derived alveolar organoid including normal and fibrosis model with three-dimensional Dynamic Optical Coherence Tomography (D-OCT). The volumetric D-OCT data were obtained by a 840-nm spectral domain OCT. And the D-OCT images were obtained by “logarithmic-intensity-variance (LIV)” method, which is sensitive to the magnitude of tissue dynamics. Cystic structures with high-LIV border and mesh-like structures with low LIV were observed in all the organoids. They correspond to alveoli and fibroblast. The LIV images also visualized the abnormal repairing process of the alveolar epithelium.

Phase-preserving Spectral Estimation Optical Coherence Tomography (SE-OCT) enables combining axial resolution improvement with computational Depth of Focus (DOF) extension. We combine SE-OCT with Interferometric Synthetic Aperture Microscopy (ISAM) to obtain a high 3D resolution over a large depth range with a narrow bandwidth visible light Super-Luminescent Diode (SLD). SE-OCT gives a five times axial resolution improvement to 1.5 micrometer. The combination with ISAM gives a sub-micron lateral resolution over a 300-micrometer axial range, 12 times the conventional DOF. The results show that phase-preserving SE-OCT is sufficiently accurate for coherent post-processing, enabling the use of cost-effective SLDs in the visible light range for high spatial resolution.

Speckle reduction has been an active topic of interest in the Optical Coherence Tomography (OCT) community and several techniques have been developed ranging from hardware-based methods, conventional image-processing and deep-learning based methods. The main goal of speckle reduction is to improve the diagnostic utility of OCT images by enhancing the image quality, thereby enhancing the visual interpretation of anatomical structures. We have previously introduced a probabilistic despeckling method based on non-local means for OCT—Tomographic Non-local-means despeckling (TNode). We demonstrated that this method efficiently suppresses speckle contrast while preserving tissue structures with dimensions approaching the system resolution. Despite the merits of this method, it is computationally very expensive: processing a typical retinal OCT volume takes a few hours. A much faster version of TNode with close to real-time performance, while keeping with the open source nature of TNode, could find much greater use in the OCT community. Deep learning despeckling methods have been proposed in OCT, including variants of conditional Generative Adversarial Networks (cGAN) and convolutional neural networks CNN. However, most of these methods have used B-scan compounding as a ground truth, which presents significant limitations in terms of speckle reduced tomograms with preservation of resolution. In addition, all these methods have focused on speckle suppression of individual B-scans, and their performance on volumetric tomograms is unclear: the expectation is that three-dimensional manipulations of these processed tomograms (i.e., en face projections) will contain artifacts due to the B-scan-wise processing, disrupting the continuity of tissue structures along the slow-scan axis. In addition, speckle suppression based on individual B-scans cannot provide the neural network with information on volumetric structures in the training data, and thus is expected to perform poorly on small structures. Indeed, most deep-learning despeckling works have focused on image quality metrics based on demonstrating strong speckle suppression, rather than focusing on preservation of contrast and small tissue structures. To overcome these problems, we propose an entire workflow to enable the wide-spread use of deep-learning speckle suppression in OCT: the ground-truth is generated using volumetric TNode despeckling, and the neural network uses a new cGAN that receives OCT partial volumes as inputs to utilize the three-dimensional structural information for speckle reduction. Because of its reliance on TNode for generating ground-truth data, this hybrid deep-learning–TNode (DL-TNode) framework will be made available to the OCT community to enable easy training and implementation in a multitude of OCT systems without relying on specialty-acquired training data.

Optical Coherence Tomography (OCT) is a powerful label-free approach for volumetric morphological imaging with numerous applications, especially within biomedicine. The penetration depth of OCT reaches well beyond conventional microscopy; however, signal reduction with depth leads to a rapid degradation of the signal below the noise level. The important pursuit of imaging at depth has been largely approached by extinguishing multiple scattering. This has been valid for many microscopies; however, here, we postulate that in OCT, multiple scattering can enhance image contrast at depth. We demonstrate this using an original geometry that completely decouples the incident and collection light fields by introducing a spatial offset between them. This approach leads to a preferential collection of multiply scattered light with depth, compensating for signal attenuation and enhancing the image contrast at depth. A wave optics model and unified theoretical framework supports our experimentally demonstrated improvement in contrast. The effective signal attenuation can be reduced by over 24 dB. Our approach reveals mesoscale features in images of ex vivo mouse bone. Considering most approaches to date have aimed to minimize multiple scattering, our results suggest that the problem of OCT imaging at depth should be distinguished from optical microscopy at depth. This facile and widely applicable geometry enables a power capacity to dynamically tune for contrast at depth.

Wavefront shaping could enable focusing light deep inside scattering media, increasing the depth and resolution of imaging techniques like optical microscopy and optical coherence tomography. However, factors like rapid decorrelation times due to microscale motion and thermal variation make focusing on living tissue difficult. A way to ease the requirements could be exploiting prior information provided by memory effects. For example, this might allow partially or wholly scanning a focus. To study this and related ideas, a computational model was developed to simulate the generation and correlations of foci formed by WFS in scattering media. Predictions of the angular memory range were consistent with experimental observations. Furthermore, correlations observed between optical phase maps required to focus on different positions suggested correlation-based priors might enable accelerated focusing. This work could pave the way to faster optical focusing and thus deeper imaging in living tissue.

In this abstract, we introduce a swpet-source Optical Coherence Tomography (OCT) and OCT Angiography (OCTA) system with a 112 Field of View (FOV) to enable high-resolution peripheral retinal imaging in rat eyes. To achieve this unprecedented FOV, a contact imaging probe for rat eye was developed. This system was demonstrated on healthy adult rats, as well as Oxygen Induced Retinopathy (OIR) rats and healthy controls with the same age. The Ultrawide-field (UWF) OCT and OCTA system could allow earlier recognition of peripheral retinal disease, such as OIR, and prevent permanent vision loss. Additionally, adequate visualization of the peripheral retina has a great potential for better understanding disease mechanisms regarding the periphery. This UWF-OCT/OCTA offers significant values in clinical retinal studies and basic vision science.

Spatio-Temporal Optical Coherence Tomography (STOC-T) is a new imaging modality that uses light with controlled spatial and temporal coherence. The retinal images acquired with the STOC-T system maintain high resolution in all three dimensions, over the entire thickness of about 700 μm, without mechanical scanning. We have employed known data processing algorithms and developed new ones to handle and process the acquired data sets to produce highly corrected 3D data for retinas over large fields of view. The technology and algorithms used here enabled high transverse resolution imaging of the retina and the choroid at various depths, making the differentiation of morphology visible for the first time within the Sattler’s, Haller’s, and choriocapillaris layers. Visualization of choroidal layers was carried out by using the STOCT angio algorithm. We analyzed the acquired data quantitatively to identify an effective biomarker.

Optical Coherence Tomography Angiography (OCTA), a functional extension of Optical Coherence Tomography (OCT), is capable of imaging blood flow signals non-invasively at the capillary level without the need for dye injection. However, widespread usage of OCTA is hindered by the trade-off between transverse sampling rate and Signal to Noise Ratio (SNR). To achieve a clinically applicable field of view, capillary fine details are commonly sacrificed due to under-sampling. In addition, the image contrast of capillaries suffers from 'thin line' motion artifacts. We introduce spectrally extended line field OCTA (SELF-OCTA) that tackles the above-mentioned issues with parallel transverse sampling and increased allowable light exposure. We show that SELF-OCTA provides significantly improved sampling density and image contrast for microvasculature compared with the standard OCTA technique.

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.

Diabetic retinopathy is the leading cause of vision loss. Optical coherence tomography-angiography is emerging as the potentially most promising technique for diagnosing DR. We circumvent the necessity for strong labels in these data with our multiple instance learning (MIL)-based network, MIL-ResNet14. MIL-ResNet14 is evaluated against two other proven capable classifiers, Res-Net14 and VGG16. All networks were assessed quantitatively by numerical classification values. MIL-ResNet14 showcased superior numerical classification abilities and turned to identify lesions more reliably. We conclude that MIL has a regularizing effect on inexactly labeled data and is a more reliable classifier than previously proposed methods.

Optical coherence tomography is a powerful imaging technique to visualize and localize depth-dependent tissue structure to differentiate between healthy and pathological conditions. However, conventional OCT systems are only capable of detecting small areas. To overcome this limitation, we have developed a large area robotically assisted OCT (LARA-OCT) system for automatic acquisition of large OCT images. Using mosaic pattern acquisition and subsequent stitching, we previously demonstrated initial in vivo OCT skin images beyond 10 cm². To improve acquisition speed and reduce dead times, we here demonstrate and analyze LARA-OCT with a new drive-by continuous motion imaging protocol.

Four-dimensional microscope integrated optical coherence tomography (4D-miOCT) has been proposed as an alternative to conventional white-light microscopy during ophthalmic surgical interventions. Its real-time visualization capability of 3D data constitutes one of the most promising visualization techniques for many surgical use cases in ophthalmology. In this work, we conducted a comprehensive user study for optimal visualization with the highest performance use of the 4D-miOCT data, comparing an autostereoscopic light field tablet to a 3D TV. With the feedback collected as part of a user study, we are able to further optimize how we display 4D-miOCT data to surgeons.

In recent years, it was demonstrated that discrimination between white matter and tumor-infiltrated white matter based on optical coherence tomography (OCT) data is possible with high accuracy. However, gray matter is also present during the tumor resection and shows similar optical properties to tumor infiltration, which aggravates the tumor classification using optical coherence tomography. A semantic segmentation approach based on a convolutional neural network was applied to the problem in order to classify healthy brain tissue from tumor infiltrated brain tissue. A dataset was created, which consisted of ex vivo OCT B-scans, which were acquired by a swept-source OCT system with a central wavelength of 1300 nm. Each OCT B-scan was indirectly annotated by transforming histological labels from a corresponding H&E section onto it. The labels differentiate between white matter, gray matter and tumor infiltration. The output of the network was modeled to a Dirichlet prior distribution, which enabled the capturing of a prediction uncertainty. This approach achieved an intersection over union score of 0.72 for healthy brain tissue and 0.69 for highly tumor infiltrated brain tissue, when only confident predictions were considered.

Optical coherence tomography can provide visualizations of the eye both in diagnostic and surgical settings. However, noise limits the achievable image quality, especially in scenarios in which multi-frame averaging is not available. In this work, we present high-quality OCT image denoising using deep learning, only requiring unpaired volumetric capture scans for training. It is shown that, by exploiting neighboring B-scans, an artificial neural network for denoising OCT images can be trained based on a state-of-the-art approach which usually requires repeated scans from the exact same location. The effect of denoising is demonstrated for B-scans and volumetric renderings during and after mock cataract surgery on ex-vivo porcine eyes.

Optical Coherence Tomography (OCT) recently attracted attention for the quality control of pharmaceutical film-coatings. Current research focuses on single-layered tablet coatings with layer thicknesses between 50 and 100 μm and production end-point detection using commercial systems available for such applications. Modern multi-particulate dosage forms, particularly interesting for pediatric and personalized medicine, show coating layer thicknesses of 20 μm and below, pushing the limits of commercial pharmaceutical industrial OCT systems, which are namely their spatial and temporal resolutions. We present a novel ultra-high-resolution (UHR-) OCT prototype investigating merits and constraints of the technology based on imaging and semi-automatic layer thickness segmentation and quantification of exemplary multi-particulate dosage forms with different layer structures and layer thicknesses in a range from seven to 50 μm. The UHR-OCT system allows, for the first time, imaging of morphological features and defects within thin pharmaceutical coatings, accurate film thickness measurements and the quantitative analyses of coating layer variability. Our investigation showcases that UHR-OCT can be the next logical and necessary step to advance quality control in pharmaceutical settings.

The absence of confocal gating in full-field Optical Coherence Tomography (OCT) worsens its dynamic range and thereby the sensitivity and signal to background noise ratio because of the inability to reject the out-of-focus and other incoherent light. Here, we present a simple and affordable confocal line scanning implementation that significantly reduces the incoherent light. We realize a fully digital line scanning that contains no moving parts, by exploiting a Digital Mirror Device (DMD) in combination with a CMOS camera running in the rolling shutter mode. An improvement of the signal to noise ratio due to the confocal line-scanning by at least an order of magnitude was demonstrated on a sample composed of the USAF target mounted behind a scattering layer. We also imaged a sample of onion epidermis with an incoherent reflector.

We introduce a phase information-based, free-of-optimization multiple spectrometers’ spectral alignment method. Our technique relies on the observation that the slope of the unwrapped phase of the interferometric signal changes linearly with the same gradient for all identical spectrometers. Our method shows the clear benefit of shorter computational time compared to previously proposed methods based on optimization algorithms. The approach presented here can be used with commercially available spectrometers in which access to optical elements is limited and physical alignment is impossible.

The leading global cause of death in children under the age of five is due to complications arising from Preterm Birth (PTB). Although it is not fully understood why PTB can happen spontaneously, it is known that the cervix’s collagen rich extracellular matrix remodels prior to both term and preterm labor. In vitro Polarization-Sensitive Optical Coherence Tomography (PS-OCT) has successfully imaged the distribution and 3D alignment of collagen in the cervix, as well as determined birefringence and measured cervical tissue depolarization in healthy tissue samples. The present investigation aims to expand on this research, by implementing in silico design, optimization, and simulation techniques for a PS-OCT probe to be used for human in vivo cervical scanning. The design considers patient comfort and clinical access as key parameters; ensuring the components are suitable for a colposcope-like probe and commercially available for quick and cost-effective manufacturing. To achieve these aims, the design benefits from using as few components as possible and limiting optical surface reflections. In this paper we demonstrate that with the use of a cemented Gradient Index (GRIN) relay system, a Field of View (FOV) of up to 6 mm can be achieved, with a back-coupling efficiency of over 73%, on-axis and at up to a 2° scanning angle. Although Huygens Point Spread Function (PSF) lateral resolution reached 81 μm, this paper demonstrates that manual adjustment and optimization of the components can increase this resolution to 12 μm, although at the expense of FOV width reduction. The simulated probe design was verified in preliminary experiments using an in-house built fiber-based OCT engine where high-quality OCT images with wide FOV were obtained from various samples, including healthy human skin.

Optical Coherence Tomography (OCT) has been widely used in many clinical apartments. The trade-off between Field-of-View (FOV) and transverse resolution has always become critical. High-Resolution (HR) image reconstruction of OCT has the potential to increase the resolution without reducing the FOV. Although it has been widely explored in these years, it is hard to find one-to-one paired high-resolution for reference. The SR methods are used to improve the cross-sectional OCT image only. Therefore, we build a custom-design, wide field-of-view, multi-scale optical coherence tomography that can allow us to produce excellent high- and low-resolution one-to-one mapping volumetric data set. With the SR methods, we can reduce the acquisition of synthetic high-resolution volumetric images by up to four times.

In this study, we present an artificial intelligence based algorithmic system that predicts missing A-scans of the edited OCT image by padding the A scan with zero. The developed artificial intelligence algorithmic system consists of two networks: convolutional neural network and generative adversarial network. The system theoretically suggests that skipping one-third of sequential A-scans and predicting the missing A-scan can increase the image acquisition rate by at least 33%. The structural similarity index measurement of the test data reaches an average of 82% between the ground truth images and the images predicted from the developed system. The mean squared error also is to 0.2%.

We present a swept source based on a Semiconductor Optical Amplifier (SOA) as a light emitter as well as a gain medium at 850 nm, equipped with a diffraction grating and a 16 kHz resonant scanner. The developed swept source is bidirectional, capable of 32 kHz operation, with a linewidth of 0.08 nm and a tuning range of 12 nm.

We developed a novel fiber-based minimalistic system for cross-polarization optical coherence tomography using polarization-maintaining fiber in the sample arm. A long section of polarization-maintaining fiber was placed in the sample arm which acted as a delay line. Co- and cross-polarized images appear at different depth positions within the image. Test measurements with a quarter-wave plate demonstrate the sensitivity of the system to the birefringence of the sample. The signal in the images is not sensitive to the bending of polarization maintaining fiber in the sample arm, making the system a promising tool for endoscopy and clinical applications.

Phase sensitive Optical Coherence Tomography (OCT) is able to measure small axial motion at the level of ten nanometer. However, when interfaces are located close to each other, the phase of one interface may influence the phase of the other interface. This spectral leakage hampers the ability to see relative motion between structures within the sample, especially when the separation is below the axial resolution. Spectral estimation OCT (SE-OCT) based on IAA can not only improve the axial resolution beyond the conventional bandwidth limitation, but also reduce this spectral leakage. Here we show accurate reconstruction of the vibration of an interface at sub-resolution distance from a high-intensity interface with a different vibration frequency. Phase preserved IAA successfully reduces spectral leakage and outperforms conventional DFT-based reconstruction methods.

Optical Coherence Tomography (OCT) is a widely used medical imaging technique for diagnosing various eye conditions and for assessing the health of the retina and other structures in the eye. As the amount of data generated from OCT scans increases day by day, the need for automated support systems for medical staff becomes more pressing. In this study, we used a computer based diagnostic system for detecting and classifying three retinal diseases Choroidal Neovascularization (CNV), Drusen, Diabetic Macular Edema (DME)) in OCT B-scans. Our system applies Convolutional Neural Networks (EfficeintNet) and Transfer learning to make accurate predictions of the diseases or healthy eye. Transfer learning, a technique commonly used in deep learning, is implemented to train EfficientNet architectures using a publicly available dataset (OCT2017) of approx 84000 OCT B-scans. EfficientNet models were chosen for their known efficiency in terms of performance and their ability to classify effectively with fewer parameters and lower computational requirements in comparison to other Convolutional Neural Networks (CNN) models. We used EfficeintNet models that were pretrained on ImageNet dataset and fine-tuned the models on our dataset. In order to assess the effectiveness of transfer learning and fine-tuning, we evaluated their performance on an imbalanced multiclass classification task using metrics like F1 Score, Precision, Recall, Accuracy, and Confusion Matrices (CM). The results of our evaluations are presented in the form of CM for each class and model. We tried out various EfficientNet models (B0, B3, B5) as base models utilizing similar data resolution, volume and other hyperparameters, and discovered that larger EfficientNet models did not necessarily lead to better classification performance. We accounted for class imbalance in the data to make our method robust for real-world scenarios. The best result was found to be from lowest complexity model, EfficientNet B0. Our research found that the EfficientNet B0 model demonstrated exceptional performance with a macro average F1 Score of 99.8% and an Accuracy of 99.8%. Additionally, our results also revealed that the EfficientNets B0, B3, B5 models are particularly well-suited for multiclass classification based on highly imbalanced OCT2017 dataset. High classification scores are achieved due to several factors, such as data enhancement, resolution scaling, fine-tuning, and successful transfer learning using ImageNet weights. Based on our preliminary results our approach performs as well or outperforms other known approaches. Our goal is to provide assistance to medical staff in diagnositic process with the help of artificial intelligence (AI) algorithms. Improving the efficiency and accuracy of diagnosis is important in the field of medicine, and the use of AI algorithms such as the one proposed in this research has the potential to make a significant impact in this regard.

In this study, a Swept-Source Optical Coherence Tomography (SS-OCT) system and a Raman fiber laser with high laser output are used to investigate the photothermal effect on biological tissue. An optical focuser is connected to the Raman fiber laser to focus the laser power on the specific area of the tissue. To simultaneously observe the induced photothermal effect, a dynamic algorithm is used in the process to produce dynamic image of the tissue from time-series OCT images. The results show that with dynamic images, we can identify the extent and area of laser ablation with time. Moreover, after merging the dynamic image and the original OCT image, we can indicate the ablated area in the tissue apart from the surrounding area without ablation.

The behavior of the signal elements in a quantum-mimic OCT is modelled to provide coefficients for simultaneous spectral calibration and dispersion compensation. The method allows to obtain the correction vectors based on a single spectrum and in an almost fully automatic way.

Blind-Structured Illumination Microscopy (blind-SIM) enhances the optical resolution without the requirement of nonlinear effects or pre-defined illumination patterns. It is thus advantageous in experimental conditions where toxicity or biological fluctuations are an issue. Here we introduce a custom convolutional neural network architecture for blind-SIM: BS-CNN. This deconvolution algorithm, based on a 3D correlation kernel, can be employed strategically together with Scattering Assisted Imaging (SAI), thus enhancing resolution also in turbid media. Indeed, in standard imaging systems spatial resolution that is ultimately dictated by the Numerical Aperture (NA) of the illumination/collection optics. In biological tissues, the resolution is strongly affected by scattering, which limits the penetration depth to tenths of microns. SAI exploit the properties of speckle patterns embedded into a strongly scattering matrix to illuminate the sample at high spatial frequency content. Combining adaptive optics with our deconvolution algorithm, we obtain a resolution improvement of 2.17 and high fidelity in the form of artifacts reductions. This multi technique approach can find applications in the retinal investigation, where numerical aperture is biologically limited by the eye iris thus limited to a maximum o 0.25. SAI plus BS-CNN can be potentially applied to the eye providing images with increased effective resolution.

In this paper, we present a Wavefront Division (WD) Fourier domain Swept Source Optical Coherence Tomography (SS-OCT) configuration. The presented WD-SS-OCT configuration has two key features that are discussed in this contribution. First, there is the possibility of variable splitting and flexible adjustment of the splitting ratio between the sample and the reference. This enables an adaptation to differing reflective and scattering features of various samples. The second feature is related to the increased throughput of the interferometer design. The use of polarization optics makes it possible to almost eliminate back-reflection losses completely to the source (up to 50% of the intensity in standard amplitude division-based OCT). WD-OCT configuration has its challenges compared to conventional OCT systems based on amplitude splitting. Nevertheless, the proposed design has also specific options and flexibilities that are worth to be shared with the OCT community.

The diagnosis and treatment of dermatological diseases has always been valued, and the laser therapy is one of the main methods for the treatment of skin diseases. Optical Coherence Tomography (OCT) is a non-invasive, label-free, high-resolution and high-speed imaging technique, which is very suitable as a diagnostic tool in dermatology. In this study, we developed an Ultrahigh-Resolution OCT system (UHR-OCT), with below 2 μm in both axial and lateral resolution in tissue. The system is implemented to observe skin microstructure and layering, and to investigate postoperative follow-up of laser therapy. The results show that the developed UHR-OCT system can clearly distinguish the microstructure and layering of the skin, meaning that the system is well-suitable for skin diagnosis. In addition, we also investigated the photodamage such as LIOB in the tracking of laser treatment, which confirmed the value of UHR-OCT system in dermatology and laser treatment.

X-rays imaging is the gold standard in dental medicine for diagnosis and treatment evaluation and monitoring. We have explored the possible synergy of different types of dental radiographies with another imaging technique, Optical Coherence Tomography (OCT). With regard to the former, the latter offers higher resolution and non-invasive imaging of the tissue structure with no radiation exposure. However, OCT has much lower penetration depth. This trade-off between various characteristics imposes one or the other of these two techniques, or in some cases both of them for different medical investigations. Thus, we have explored the integration of these two imaging modalities, which can provide improved visualization of the tissue structure, enhance diagnostic accuracy, and reduce patient radiation dose. Also, we demonstrated that OCT can successfully serve as an optimization technique for various types of radiographies. This report is focused on such optimizations performed for dental 3D Cone-Beam Computed Tomography (CBCT). The use of CBCT X-ray units in dentistry imaging has revolutionized the way images are captured and processed. However, these units often suffer from low image quality, limited tissue visualization, and exposure to ionizing radiation. While CBCT images are useful for dental diagnosis and planning, they can be limited by poor tissue contrast and a lack of information about the internal structure of the tissues being imaged. We present how the integration of OCT in the process of optimization of CBCT X-ray units allows for real-time imaging of the tissue with improved accuracy and resolution. This combination provides dentists with detailed images of the tooth, jaw, and surrounding tissues, which enables better diagnosis and treatment planning. In conclusion, the optimization of CBCT X-ray units with OCT can be a step forward in the field of medical imaging. This combination can provide a more comprehensive, accurate, and non-invasive approach to tissue imaging that benefits both patients and healthcare professionals.