This article presents new developments in a multiframe blind deconvolution algorithm for imaging low earth orbiting objects during flyover. The foundational aspects of the algorithm rely on the constrained maximum likelihood (ML) formulation in the presence of Poisson noise, previously developed in Schulz et al. (2018). The new algorithm achieves real time evaluation capability at over two frames per second, which is allowed by two novel aspects. First, the prototype algorithms are transferred to highly parallelized computations on graphical processing units (GPUs) with CUDA implementation that reduce the computational time of a single iteration by a factor of up to 100. Second, new numerical optimization strategies are developed and demonstrated to accelerate the convergence of the algorithm by a factor of 5 to 10. Several other new capabilities are also demonstrated in this article. We derive and implement a modified variation of the algorithm that achieves subpixel resolution, which is shown effective on real and simulated data. Finally, a new post-processing visual enhancement technique is proposed with several examples, which in part helps deal with the dynamic range degradation due to glint.

Recent advances are presented for multiframe blind deconvolution (MFBD) of ground based telescope imagery for low-earth orbit objects. The iterative algorithm uses the maximum likelihood estimation optimization criterion. It is modeled from a previous well-known algorithm called the expectation-maximization (EM) algorithm. New renditions of the algorithm simplify the phase reconstruction, thereby reducing the complexity of the original EM algorithm. Examples are shown, with and without adaptive optics (AO). The system is being designed for on-the-fly streaming video operation.

Recent advances in multiframe blind deconvolution of ground based telescopes are presented. The paper focuses on practical aspects of the software and algorithm. (1) A computer simulation that models atmospheric turbulence, noise and other aspects, for testing and evaluation of the deconvolution system are explained. (2) A post-processing algorithm that corrects for glint due to specular and other bright reflections is presented. This glint correction is automated by a spatially adaptive scheme that calculates statistics of brightness levels. (3) Efforts to realize computational speed, wherein processing happens on-the-fly at streaming frame rates are underway. The massively parallel processing of graphical processing units (GPUs) and the Compute Unified Device Architecture (CUDA) language are used.

3D image reconstruction using light microscope modalities without exogenous contrast agents is proposed and investigated as an approach to produce 3D images of biological samples for live imaging applications. Multimodality and multispectral imaging, used in concert with this 3D optical sectioning approach is also proposed as a way to further produce contrast that could be specific to components in the sample. The methods avoid usage of contrast agents. Contrast agents, such as fluorescent or absorbing dyes, can be toxic to cells or alter cell behavior. Current modes of producing 3D image sets from a light microscope, such as 3D deconvolution algorithms and confocal microscopy generally require contrast agents. Zernike phase contrast (ZPC), transmitted light brightfield (TLB), darkfield microscopy and others can produce contrast without dyes. Some of these modalities have not previously benefitted from 3D image reconstruction algorithms, however. The 3D image reconstruction algorithm is based on an underlying physical model of scattering potential, expressed as the sample's 3D absorption and phase quantities. The algorithm is based upon optimizing an objective function - the I-divergence - while solving for the 3D absorption and phase quantities. Unlike typical deconvolution algorithms, each microscope modality, such as ZPC or TLB, produces two output image sets instead of one. Contrast in the displayed image and 3D renderings is further enabled by treating the multispectral/multimodal data as a feature set in a mathematical formulation that uses the principal component method of statistics.

It is generally believed that photoreceptor integrity is related to the ellipsoid zone appearance in optical coherence tomography (OCT) B-scans. Algorithms and software were developed for viewing and analyzing the ellipsoid zone. The software performs the following: (a), automated ellipsoid zone isolation in the B-scans, (b), en-face view of the ellipsoid-zone reflectance, (c), alignment and overlay of (b) onto reflectance images of the retina, and (d), alignment and overlay of (c) with microperimetry sensitivity points. Dataset groups were compared from normal and dry age related macular degeneration (DAMD) subjects. Scalar measurements for correlation against condition included the mean and standard deviation of the ellipsoid zone's reflectance. The imageprocessing techniques for automatically finding the ellipsoid zone are based upon a calculation of optical flow which tracks the edges of laminated structures across an image. Statistical significance was shown in T-tests of these measurements with the population pools separated as normal and DAMD subjects. A display of en-face ellipsoid-zone reflectance shows a clear and recognizable difference between any of the normal and DAMD subjects in that they show generally uniform and nonuniform reflectance, respectively, over the region near the macula. Regions surrounding points of low microperimetry (mu P) sensitivity have nonregular and lower levels of ellipsoid-zone reflectance nearby. These findings support the idea that the photoreceptor integrity could be affecting both the ellipsoid-zone reflectance and the sensitivity measurements.

Three-dimensional (3D) cell culture assays are important tools in the study of vessel assembly. Current techniques for quantitative analysis of vascular network structure have provided important insight into 3D vessel assembly. However, these methods typically require immunohistochemical staining, which requires sample destruction, or fluorescent cell labeling, which may alter cell behavior. The methods also may require sophisticated and expensive microscopy. More robust, easily quantifiable techniques are needed for imaging vascular networks non-invasively. We present an imaging method based on widefield optical sectioning and digital deconvolution (WOSD) that enables imaging of vascular networks in 3D culture without the use of cell labeling, staining, or sample destruction. WOSD can be performed using a standard optical microscope and allows non-invasive 3D monitoring of vascular network formation. This method is illustrated by imaging vascular networks in a 3D hydrogel system. WOSD enabled production of quantifiable 3D images of the network structure. Accuracy of the technique was evaluated by comparing data from WOSD with confocal images of fixed and fluorescently stained samples. Data for vessel length, diameter, and density are consistent between the two methods. The WOSD approach can be applied using standard laboratory equipment and shows great promise for use in analysis of 3D vascular network formation.

Dynamic indocyanine green imaging uses a scanning laser ophthalmoscope and a fluorescent dye to produce movies of the dye-filling pattern in the retina and choroid of the eye. It is used for evaluating choroidal neovascularization. Movies are examined to identify the anatomy of the pathology for planning treatment and to evaluate progression or response to treatment. The popularity of this approach is affected by the complexity and difficulty in interpreting the movies. Software algorithms were developed to produce images from the movies that are easy to interpret. A mathematical model is formulated of the flow dynamics, and a fitting algorithm is designed that solves for the flow parameters. The images provide information about flow and perfusion, including regions of change between examinations. Imaged measures include the dye fill-time, temporal dispersion, and magnitude of the dye dilution temporal curves associated with image pixels. Cases show how the software can help to identify clinically relevant anatomy such as feeder vessels, drain vessels, capillary networks, and normal choroidal draining vessels. As a potential tool for research into the character of neovascular conditions and treatments, it reveals the flow dynamics and character of the lesion. Future varieties of this methodology may be used for evaluating the success of engineered tissue transplants, surgical flaps, reconstructive surgery, breast surgery, and many other surgical applications where flow, perfusion, and vascularity of tissue are important.

A fundus camera is an optical system designed to illuminate and image the retina while minimizing stray light and back-reflections. Modifying such a device requires characterization of the optical path in order to meet the new design goals and avoid introducing problems. This work describes the characterization of one system, the Topcon TRC-50F, necessary for converting this camera from film photography to spectral imaging with a CCD. This conversion consists of replacing the camera's original xenon flash tube with a monochromatic light source and the film back with a CCD. A critical preliminary step of this modification is determining the spectral throughput of the system, from source to sensor, and ensuring there are sufficient photons at the sensor for imaging. This was done for our system by first measuring the transmission efficiencies of the camera's illumination and imaging optical paths with a spectrophotometer. Combining these results with existing knowledge of the eye's reflectance, a relative sensitivity profile is developed for the system. Image measurements from a volunteer were then made using a few narrowband sources of known power and a calibrated CCD. With these data, a relationship between photoelectrons/pixel collected at the CCD and narrowband illumination source power is developed.

Movies acquired from fundus imaging using Indocyanine Green (ICG) and a scanning laser ophthalmoscope provide information for identifying vascular and other retinal abnormalities. Today, the main limitation of this modality is that it requires esoteric training for interpretation. A straightforward interpretation of these movies by objective measurements would aid in eliminating this training barrier. A software program has been developed and tested that produces and visualizes 2D maps of perfusion measures. The program corrects for frame-to-frame misalignment caused by eye motion, including rigid misalignment and warp. The alignment method uses a cross-correlation operation that automatically detects the distance due to motion between adjacent frames. The d-ICG movie is further corrected by removing flicker and vignetting artifacts. Each pixel in the corrected movie sequence is fit with a least-squares spline to yield a smooth intensity temporal profile. From the dynamics of these intensity curves, several perfusion measures are calculated. The most effective of these measures include a metric that represents the amount of time required for a vessel to fill with dye, a metric that represents the diffusion of dye, and a metric that is affected by local blood volume. These metrics are calculated from movies acquired before and after treatment for a neovascular condition. A comparison of these before and after measures may someday provide information to the clinician that helps them to evaluate disease progression and response to treatment.

Purpose.: A relationship has been reported between the presence of peripheral neuropathy and the density and shape of corneal nerve fibers. Peripheral neuropathy is a debilitating condition that arises from many common health problems, and its presence is often confirmed with an invasive clinical test called intramuscular electromyography (EMG). In this study, the possibility of developing an alternative or adjunct test to EMG based on the appearance of nerve fibers in corneal micrographs was explored. Since corneal imaging is virtually noninvasive compared with EMG, such a test may be administered more liberally and frequently, before neuropathy symptoms occur. Methods.: A software program that automatically traces nerve fibers in corneal micrographs and generates measures based on these traces was implemented. This software was applied to a database of images collected by confocal laser scanning corneal microscopy from diabetic subjects whose levels of neuropathy were measured with EMG and from healthy subjects. Results.: Trends in the nerve fiber density and various measures of shape were calculated and observed, to explore the possibility of using these measures as a clinical tool for corroborating symptoms, confirming an evaluation, or evaluating risk factors for developing neuropathy. Conclusions.: Preliminary statistical trends show a potential for measuring and observing neuropathy severity or for providing an objective risk measure for a patient's ensuing condition. More work is needed in the development of the measures and in their testing to prove that the measures can be made repeatable in a clinical environment.

A relationship has been reported by several research groups [1 - 4] between the density and shapes of nerve fibers in the cornea and the existence and severity of peripheral neuropathy. Peripheral neuropathy is a complication of several prevalent diseases or conditions, which include diabetes, HIV, prolonged alcohol overconsumption and aging. A common clinical technique for confirming the condition is intramuscular electromyography (EMG), which is invasive, so a noninvasive technique like the one proposed here carries important potential advantages for the physician and patient.A software program that automatically detects the nerve fibers, counts them and measures their shapes is being developed and tested. Tests were carried out with a database of subjects with levels of severity of diabetic neuropathy as determined by EMG testing. Results from this testing, that include a linear regression analysis are shown.