High-speed scanning in optical coherence tomography (OCT) often comes with either compromises in image quality, the requirement for post-processing of the acquired images, or both. We report on distortion-free OCT volumetric imaging with a dual-axis micro-electro-mechanical system (MEMS)-based handheld imaging probe. In the context of an imaging probe with optics located between the 2D MEMS and the sample, we report in this paper on how pre-shaped open-loop input signals with tailored non-linear parts were implemented in a custom control board and, unlike the sinusoidal signals typically used for MEMS, achieved real-time distortion-free imaging without post-processing. The MEMS mirror was integrated into a compact, lightweight handheld probe. The MEMS scanner achieved a 12-fold reduction in volume and 17-fold reduction in weight over a previous dual-mirror galvanometer-based scanner. Distortion-free imaging with no post-processing with a Gabor-domain optical coherence microscope (GD-OCM) with 2 μm axial and lateral resolutions over a field of view of 1 × 1 mm2 is demonstrated experimentally through volumetric images of a regular microscopic structure, an excised human cornea, and in vivo human skin.
Gabor-domain optical coherence microscopy (GD-OCM) was applied ex vivo in the investigation of corneal cells and their surrounding microstructures with particular attention to the corneal endothelium. Experiments using fresh pig eyeballs, excised human corneal buttons from patients with Fuchs’ endothelial dystrophy (FED), and healthy donor corneas were conducted. Results show in a large field of view () high definition images of the different cell types and their surrounding microstructures through the full corneal thickness at both the central and peripheral locations of porcine corneas. Particularly, an image of the endothelial cells lining the bottom of the cornea is highlighted. As compared to healthy human corneas, the corneas of individuals with FED show characteristic microstructural alterations of the Descemet’s membrane and increased size and number of keratocytes. The GD-OCM-based imaging system developed may constitute a novel tool for corneal imaging and disease diagnosis. Also, importantly, it may provide insights into the mechanism of corneal physiology and pathology, particularly in diseases of the corneal endothelium.
We propose a fast algorithm to estimate the flux collected by conic reflector patches, based on the calculation of intersections between neighboring patches. The algorithm can be employed in conjunction with the supporting ellipsoids algorithm for freeform reflector design and is shown to be orders of magnitude faster and more scalable than the commonly used Monte Carlo ray tracing approach.
We implemented the linear programming approach proposed by Oliker and by Wang to solve the single reflector problem for a point source and a far-field target. The algorithm was shown to produce solutions that aim the input rays at the intersections between neighboring reflectors. This feature makes it possible to obtain the same reflector with a low number of rays - of the order of the number of targets - as with a high number of rays, greatly reducing the computation complexity of the problem.
Gabor-domain optical coherence microscopy (GDOCM) demonstrated in vivo corneal imaging with cellular resolution and differentiation in mice over a field of view of 1 mm2. Contact and non-contact imaging was conducted on six healthy and six hyperglycemic C57BL/6J mice. Cellular resolution in the 3D GDOCM images was achieved after motion correction. Corneal nerve fibers were traced and their lengths and branches calculated. Noncontact, label-free imaging of corneal nerves has clinical utility in health and disease, and in transplant evaluation. To the authors’ knowledge, this is the first report of in vivo 3D corneal imaging in mice with the capability to resolve nerve fibers using a non-contact imaging modality.
Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing.