Fast and Artifact-Free Excitation Multiplexing Using Synchronized Image Scanning.

Multicolor fluorescence microscopy is an essential tool to visualize structures and dynamics in the life and materials sciences. However, the near-simultaneous acquisition of labels differing in excitation spectrum is difficult and renders such measurements prone to artifacts. We present a simple strategy to provide quasi-simultaneous fluorescence imaging with multiple excitation wavelengths by using an optical element to displace the sample image on the sensor at a rate that is much faster than the image acquisition rate and synchronizing this with the illumination. The emission elicited by the different wavelengths can then be encoded into the point-spread function of the imaging or visualized as multiple distinct images. In doing so, our approach can eliminate or mitigate artifacts caused by temporal aliasing in conventional sequential imaging. We demonstrate the use of our system to uncover hidden emissive states in single quantum dots and for the imaging of Ca2+ signaling in neurons.

HoloTile light engine: new digital holographic modalities and applications.

HoloTile is a patented computer generated holography approach with the aim of reducing the speckle noise caused by the overlap of the non-trivial physical extent of the point spread function in Fourier holographic systems from adjacent frequency components. By combining tiling of phase-only of rapidly generated sub-holograms with a PSF-shaping phase profile, each frequency component-or output 'pixel'- in the Fourier domain is shaped to a desired non-overlapping profile. In this paper, we show the high-resolution, speckle-reduced reconstructions that can be achieved with HoloTile, as well as present new HoloTile modalities, including an expanded list of PSF options with new key properties. In addition, we discuss numerous applications for which HoloTile, its rapid hologram generation, and the new PSF options may be an ideal fit, including optical trapping and manipulation of particles, volumetric additive printing, information transfer and quantum communication.

Fast and silent MRI using nonlinear gradient fields at the ultrasonic gradient switching frequency of 20 kHz with a Point Spread Function framework reconstruction.

PURPOSE: To demonstrate the feasibility of using a nonlinear gradient field for spatial encoding at the ultrasonic switching frequency of 20 kHz and present a framework to reconstruct data acquired in this way. METHODS: Nonlinear encoding at 20 kHz was realized by using a single-axis silent gradient insert for imaging in the periphery, that, is the nonlinear region, of the gradient field. The gradient insert induces a rapidly oscillating gradient field in the phase-encode direction, which enables nonlinear encoding when combined with a Cartesian readout from the linear whole-body gradients. Data from a 2D gradient echo sequence were reconstructed using a point spread function (PSF) framework. Accelerated scans were also simulated via retrospective undersampling (R = 1 to R = 8) to determine the effectiveness of the PSF-framework for accelerated imaging. RESULTS: Using a nonlinear gradient field switched at 20 kHz and the PSF-framework resulted in images of comparable quality to images from conventional Cartesian linear encoding. At increased acceleration factors (R ≤ 8), the PSF-framework outperformed linear SENSE reconstructions by improved controlling of aliasing artifacts. CONCLUSION: Using the PSF-framework, images of comparable quality to conventional SENSE reconstructions are possible via combining traditional linear and ultrasonic oscillating nonlinear encoding fields. Using nonlinear gradient fields relaxes the demand for strictly linear gradient fields, enabling much higher slew rates with a reduced risk of peripheral nerve stimulation or cardiac stimulation, which could aid in extension to ultrasonic whole-body MRI. The lack of aliasing artifacts also highlights the potential of accelerated imaging using the PSF-framework.

Comprehensive assessment of nonuniform image quality: Application to imaging near metal.

PURPOSE: Comprehensive assessment of image quality requires accounting for spatial variations in (i) intensity artifact, (ii) geometric distortion, (iii) signal-to-noise ratio (SNR), and (iv) spatial resolution, among other factors. This work presents an ensemble of methods to meet this need, from phantom design to image analysis, and applies it to the scenario of imaging near metal. METHODS: A modular phantom design employing a gyroid lattice is developed to enable the co-registered volumetric quantitation of image quality near a metallic hip implant. A method for measuring spatial resolution by means of local point spread function (PSF) estimation is presented and the relative fitness of gyroid and cubic lattices is examined. Intensity artifact, geometric distortion, and SNR maps are also computed. Results are demonstrated with 2D-FSE and MAVRIC-SL scan protocols on a 3T MRI scanner. RESULTS: The spatial resolution method demonstrates a worst-case error of 0.17 pixels for measuring in-plane blurring up to 3 pixels (full width at half maximum). The gyroid outperforms a cubic lattice design for the local PSF estimation task. The phantom supports four configurations toggling the presence/absence of both metal and structure with good spatial correspondence for co-registered analysis of the four quality factors. The marginal scan time to evaluate one scan protocol amounts to five repetitions. The phantom design can be fabricated in 2 days at negligible material cost. CONCLUSION: The phantom and associated analysis methods can elucidate complex image quality trade-offs involving intensity artifact, geometric distortion, SNR, and spatial resolution. The ensemble of methods is suitable for benchmarking imaging performance near metal.

From Molecules to Classrooms: A Comprehensive Guide to Single-Molecule Localization Microscopy.

Single-molecule localization microscopy (SMLM) has revolutionized our ability to visualize cellular structures, offering unprecedented detail. However, the intricate biophysical principles that underlie SMLM can be daunting for newcomers, particularly undergraduate and graduate students. To address this challenge, we introduce the fundamental concepts of SMLM, providing a solid theoretical foundation. In addition, we have developed an intuitive graphical interface APP that simplifies these core concepts, making them more accessible for students. This APP clarifies how super-resolved images are fitted and highlights the crucial factors determining image quality. Our approach deepens students' understanding of SMLM by combining theoretical instruction with practical learning. This development equips them with the skills to carry out single-molecule super-resolved experiments and explore the microscopic world beyond the diffraction limit.

The effect of transepithelial corneal collagen cross-linking treatment on optical quality of the cornea in keratoconus: 12-month clinical results.

PURPOSE: To evaluate the effect of transepithelial corneal collagen crosslinking (CXL) treatment on the optical performance of the cornea at 12-month follow-up after CXL in patients with progressive keratoconus. METHODS: One hundred and ten eyes of 67 patients were included. The following corneal optical aberrations over the 4-mm-diameter pupil were recorded via Sirius dual-scanning corneal tomography: total, anterior and posterior amount of corneal higher order aberrations [HOAs], vertical coma, horizontal coma, vertical trefoil, oblique trefoil, and spherical aberration, and Strehl ratio of point spread function (PSF). RESULTS: There were significant improvements in mean root mean square error values for corneal total HOA, total coma, anterior HOA, anterior coma, and vertical coma following CXL (P > 0.05, for all). No significant changes were found in the posterior aberometric parameters. PSF value did not change after CXL (P > 0.05). The corneal topographic measurements not revealed a change in the mean simulated keratometry-1, simulated keratometry-2, and maximum keratometry compared with the baseline measurements (P > 0.05, for all). At 12 months, there was a significant improvement in the uncorrected (UCVA) and best corrected (BCVA) visual acuity (P < 0.001, both). Most corneal aberrations correlated significantly with postoperative BCVA, but changes in HOAs were not statistically associated with improvements in visual acuity. CONCLUSIONS: Transepithelial CXL was effective in stabilizing the keratometric indices and improving the most corneal aberrations in keratoconic eyes 1 year after the procedure. While the healing effect on aberrations after CXL was in total and anterior parameters, no significant changes were observed in the posterior surface. In addition, it was observed that transepithelial CXL treatment did not cause a significant change in PSF distribution data.

Optimized flip angle schemes for the split acquisition of fast spin-echo signals (SPLICE) sequence and application to diffusion-weighted imaging.

PURPOSE: The diffusion-weighted SPLICE (split acquisition of fast spin-echo signals) sequence employs split-echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T 2 $$ {}_2 $$ -weighting during k-space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal-to-noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE. METHODS: An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k-space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post-processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner. RESULTS: Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k-space weighting example, considerable benefits resulted from acquisition weighting by flip angle control. CONCLUSION: The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion-weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery.

Simultaneous superresolution reconstruction and distortion correction for single-shot EPI DWI using deep learning.

PURPOSE: Single-shot (SS) EPI is widely used for clinical DWI. This study aims to develop an end-to-end deep learning-based method with a novel loss function in an improved network structure to simultaneously increase the resolution and correct distortions for SS-EPI DWI. THEORY AND METHODS: Point-spread-function (PSF)-encoded EPI can provide high-resolution, distortion-free DWI images. A distorted image from SS-EPI can be described as the convolution between a PSF function with a distortion-free image. The deconvolution process to recover the distortion-free image can be achieved with a convolution neural network, which also learns the mapping function between low-resolution SS-EPI and high-resolution reference PSF-EPI to achieve superresolution. To suppress the oversmoothing effect, we proposed a modified generative adversarial network structure, in which a dense net with gradient map guidance and a multilevel fusion block was used as the generator. A fractional anisotropy loss was proposed to utilize the diffusion anisotropy information among diffusion directions. In vivo brain DWI data were used to test the proposed method. RESULTS: The results show that distortion-corrected high-resolution DWI images with restored structural details can be obtained from low-resolution SS-EPI images by taking advantage of the high-resolution anatomical images. Additionally, the proposed network can improve the quantitative accuracy of diffusion metrics compared with previously reported networks. CONCLUSION: Using high-resolution, distortion-free EPI-DWI images as references, a deep learning-based method to simultaneously increase the perceived resolution and correct distortions for low-resolution SS-EPI was proposed. The results show that DWI image quality and diffusion metrics can be improved.

Enhanced Scanning Electron Microscopy Using Auto-Optimized Image Restoration With Constrained Least Squares Filter for Nanoscience.

The growing demands of nanoscience require the continuous improvement of visualization methods. The imaging performance of scanning electron microscopy (SEM) is fundamentally limited by the point spread function of the electron beam and degrades because of noise. This paper proposes an auto-optimization algorithm based on deconvolution for the restoration of SEM images. This algorithm uses a constrained least squares filter and does not dependent on the user's experience or the availability of nondegraded images. The proposed algorithm improved the quality of the SEM images of 10-nm Au nanoparticles, and achieved balance among the sharpness, contrast-to-noise ratio (CNR), and image artifacts. For the SEM image of 100-nm pitched line patterns, the analysis of the spatial frequencies allowed the 2.5-fold improvement of the intensity of 4-nm information, and the noise floor decreased approximately 32 times. Along with the results obtained by the application of the proposed algorithm to images of tungsten disulfide (WS2) flakes, carbon nanotubes (CNTs), and HeLa cells, the evaluation results confirm that the proposed algorithm can enhance the SEM imaging of nanoscale features that lie close to the microscope's resolution limit.

Tissue-Like 3D Standard and Protocols for Microscope Quality Management.

This article outlines a global study conducted by the Association of Biomedical Resource Facilities (ABRF) Light Microscopy Research Group (LMRG). The results present a novel 3D tissue-like biologically relevant standard sample that is affordable and straightforward to prepare. Detailed sample preparation, instrument-specific image acquisition protocols and image analysis methods are presented and made available to the community. The standard consists of sub-resolution and large well characterized relative intensity fluorescence microspheres embedded in a 120 µm thick 3D gel with a refractive index of 1.365. The standard allows the evaluation of several properties as a function of depth. These include the following: 1) microscope resolution with automated analysis of the point-spread function (PSF), 2) automated signal-to-noise ratio analysis, 3) calibration and correction of fluorescence intensity loss, and 4) quantitative relative intensity. Results demonstrate expected refractive index mismatch dependent losses in intensity and resolution with depth, but the relative intensities of different objects at similar depths are maintained. This is a robust standard showing reproducible results across laboratories, microscope manufacturers and objective lens types (e.g., magnification, immersion medium). Thus, these tools will be valuable for the global community to benchmark fluorescence microscopes and will contribute to improved scientific rigor and reproducibility.

Quantitative Analysis of Super Resolution in Electromagnetic Inverse Scattering for Microwave Medical Sensing and Imaging.

Microwave medical sensing and imaging (MMSI) has been a research hotspot in the past years. Imaging algorithms based on electromagnetic inverse scattering (EIS) play a key role in MMSI due to the super-resolution phenomenon. EIS problems generally employ far-field scattered data to reconstruct images. However, the far-field data do not include information outside the Ewald's sphere, so theoretically it is impossible to achieve super resolution. The reason for super resolution has not been clarified. The majority of the current research focuses on how nonlinearity affects the super-resolution phenomena in EIS. However, the mechanism of super-resolution in the absence of nonlinearity is routinely ignored. In this research, we address a prevalent yet overlooked problem where the image resolution due to scatterers of extended structures is incorrectly analyzed using the model of point scatterers. Specifically, the classical resolution of EIS is defined by the Rayleigh criterion which is only suitable for point-like scatterers. However, the super-resolution in EIS is often observed for general scatterers like cylinders, squares or Austria shapes. Subsequently, we provide theoretical results for the Born approximation framework in EIS, and employ the Sparrow criteria to quantify the resolution for symmetric objects of extended structures. Furthermore, the modified Sparrow criterion is proposed to calculate the resolution of asymmetric scatterers. Numerical examples show that the proposed approach can better explain the super-resolution phenomenon in EIS.

Discovery, Quantitative Recurrence, and Inhibition of Motion-Blur Hysteresis Phenomenon in Visual Tracking Displacement Detection.

Motion blur is common in video tracking and detection, and severe motion blur can lead to failure in tracking and detection. In this work, a motion-blur hysteresis phenomenon (MBHP) was discovered, which has an impact on tracking and detection accuracy as well as image annotation. In order to accurately quantify MBHP, this paper proposes a motion-blur dataset construction method based on a motion-blur operator (MBO) generation method and self-similar object images, and designs APSF, a MBO generation method. The optimized sub-pixel estimation method of the point spread function (SPEPSF) is used to demonstrate the accuracy and robustness of the APSF method, showing the maximum error (ME) of APSF to be smaller than others (reduced by 86%, when motion-blur length > 20, motion-blur angle = 0), and the mean square error (MSE) of APSF to be smaller than others (reduced by 65.67% when motion-blur angle = 0). A fast image matching method based on a fast correlation response coefficient (FAST-PCC) and improved KCF were used with the motion-blur dataset to quantify MBHP. The results show that MBHP exists significantly when the motion blur changes and the error caused by MBHP is close to half of the difference of the motion-blur length between two consecutive frames. A general flow chart of visual tracking displacement detection with error compensation for MBHP was designed, and three methods for calculating compensation values were proposed: compensation values based on inter-frame displacement estimation error, SPEPSF, and no-reference image quality assessment (NR-IQA) indicators. Additionally, the implementation experiments showed that this error can be reduced by more than 96%.

No-Reference Quality Assessment of Extended Target Adaptive Optics Images Using Deep Neural Network.

This paper proposes a supervised deep neural network model for accomplishing highly efficient image quality assessment (IQA) for adaptive optics (AO) images. The AO imaging systems based on ground-based telescopes suffer from residual atmospheric turbulence, tracking error, and photoelectric noise, which can lead to varying degrees of image degradation, making image processing challenging. Currently, assessing the quality and selecting frames of AO images depend on either traditional IQA methods or manual evaluation by experienced researchers, neither of which is entirely reliable. The proposed network is trained by leveraging the similarity between the point spread function (PSF) of the degraded image and the Airy spot as its supervised training instead of relying on the features of the degraded image itself as a quality label. This approach is reflective of the relationship between the degradation factors of the AO imaging process and the image quality and does not require the analysis of the image's specific feature or degradation model. The simulation test data show a Spearman's rank correlation coefficient (SRCC) of 0.97, and our method was also validated using actual acquired AO images. The experimental results indicate that our method is more accurate in evaluating AO image quality compared to traditional IQA methods.

Development of Adaptive Point-Spread Function Estimation Method in Various Scintillation Detector Thickness for X-ray Imaging.

An indirect conversion X-ray detector uses a scintillator that utilizes the proportionality of the intensity of incident radiation to the amount of visible light emitted. A thicker scintillator reduces the patient's dose while decreasing the sharpness. A thin scintillator has an advantage in terms of sharpness; however, its noise component increases. Thus, the proposed method converts the spatial resolution of radiographic images acquired from a normal-thickness scintillation detector into a thin-thickness scintillation detector. Note that noise amplification and artifacts were minimized as much as possible after non-blind deconvolution. To accomplish this, the proposed algorithm estimates the optimal point-spread function (PSF) when the structural similarity index (SSIM) and feature similarity index (FSIM) are the most similar between thick and thin scintillator images. Simulation and experimental results demonstrate the viability of the proposed method. Moreover, the deconvolution images obtained using the proposed scheme show an effective image restoration method in terms of the human visible system compared to that of the traditional PSF measurement technique. Consequently, the proposed method is useful for restoring degraded images using the adaptive PSF while preventing noise amplification and artifacts and is effective in improving the image quality in the present X-ray imaging system.

Evaluation of the Resolution in Inverse Scattering of Dielectric Cylinders for Medical Applications.

The inverse scattering problem has numerous significant applications, including in geophysical explorations, medical imaging, and radar imaging. To achieve better performance of the imaging system, theoretical knowledge of the resolution of the algorithm is required for most of these applications. However, analytical investigations about the resolution presently feel inadequate. In order to estimate the achievable resolution, we address the point spread function (PSF) evaluation of the scattered field for a single frequency and the multi-view case both for the near and the far fields and the scalar case when the angular domain of the incident field and observation ranges is a round angle. Instead of the common free space condition, an inhomogeneous background medium, consisting of a homogeneous dielectric cylinder with a circular cross-section in free space, is assumed. In addition, since the exact evaluation of the PSF can only be accomplished numerically, an analytical approximation of the resolution is also considered. For the sake of its comparison, the truncated singular value decomposition (TSVD) algorithm can be used to implement the exact PSF. We show how the behavior of the singular values and the resolution change by varying the permittivity of the background medium. The usefulness of the theoretical discussion is demonstrated in localizing point-like scatterers within a dielectric cylinder, so mimicking a scenario that may occur in breast cancer imaging. Numerical results are provided to validate the analytical investigations.

Towards an objective evaluation of EEG/MEG source estimation methods - The linear approach.

The spatial resolution of EEG/MEG source estimates, often described in terms of source leakage in the context of the inverse problem, poses constraints on the inferences that can be drawn from EEG/MEG source estimation results. Software packages for EEG/MEG data analysis offer a large choice of source estimation methods but few tools to experimental researchers for methods evaluation and comparison. Here, we describe a framework and tools for objective and intuitive resolution analysis of EEG/MEG source estimation based on linear systems analysis, and apply those to the most widely used distributed source estimation methods such as L2-minimum-norm estimation (L2-MNE) and linearly constrained minimum variance (LCMV) beamformers. Within this framework it is possible to define resolution metrics that define meaningful aspects of source estimation results (such as localization accuracy in terms of peak localization error, PLE, and spatial extent in terms of spatial deviation, SD) that are relevant to the task at hand and can easily be visualized. At the core of this framework is the resolution matrix, which describes the potential leakage from and into point sources (point-spread and cross-talk functions, or PSFs and CTFs, respectively). Importantly, for linear methods these functions allow generalizations to multiple sources or complex source distributions. This paper provides a tutorial-style introduction into linear EEG/MEG source estimation and resolution analysis aimed at experimental (rather than methods-oriented) researchers. We used this framework to demonstrate how L2-MNE-type as well as LCMV beamforming methods can be evaluated in practice using software tools that have only recently become available for routine use. Our novel methods comparison includes PLE and SD for a larger number of methods than in similar previous studies, such as unweighted, depth-weighted and normalized L2-MNE methods (including dSPM, sLORETA, eLORETA) and two LCMV beamformers. The results demonstrate that some methods can achieve low and even zero PLE for PSFs. However, their SD as well as both PLE and SD for CTFs are far less optimal for all methods, in particular for deep cortical areas. We hope that our paper will encourage EEG/MEG researchers to apply this approach to their own tasks at hand.

Synchrotron radiation X-ray imaging with large field of view and high resolution using micro-scanning method.

In synchrotron radiation X-ray imaging, the imaging field of view and spatial resolution are mutually restricted, which makes it impossible to have both a large field of view and high resolution when carrying out experiments. Constructing an oversampled image through the micro-scanning method and using the deconvolution algorithm to eliminate the point spread function introduced by pixel overlap can increase the resolution under a fixed imaging field of view, thereby improving the ratio of the field of view to the spatial resolution. In this paper, numerical simulation and synchrotron radiation experiments are carried out with a different number of micro-scanning steps. In numerical simulation experiments only affected by the image pixel size, as the number of micro-scanning steps increases, the ability of the oversampled image with deconvolution to improve the resolution is stronger. The achievable resolution of the oversampled image with deconvolution is basically the same as that of the sample image. In the synchrotron radiation experiments, the resolution of the oversampled image with deconvolution in the 2 × 2 mode is significantly improved. However, as the number of micro-scanning steps increases, the resolution improvement is limited, or even no longer improved. Finally, by analyzing the results of numerical simulation and synchrotron radiation experiments, three factors (four other factors affecting the resolution besides the camera resolution, translational accuracy of micro-scanning, and the signal-to-noise ratio of projections) affecting the micro-scanning method are proposed and verified by experiments.

Ultrafast B1 mapping with RF-prepared 3D FLASH acquisition: Correcting the bias due to T1 -induced k-space filtering effect.

PURPOSE: The traditional radiofrequency (RF)-prepared B1 mapping technique consists of one scan with an RF preparation module for flip angle-encoding and a second scan without this module for normalizing. To reduce the T1 -induced k-space filtering effect, this method is limited to 2D FLASH acquisition with a two-parameter method. A novel 3D RF-prepared three-parameter method for ultrafast B1 -mapping is proposed to correct the T1 -induced quantification bias. THEORY: The point spread function analysis of FLASH shows that the prepared longitudinal magnetization before the FLASH acquisition and the image signal obeys a linear (not proportional) relationship. The intercept of the linear function causes the quantification bias and can be captured by a third saturated scan. METHODS: Using the 2D double-angle method (DAM) as the reference, a 3D RF-prepared three-parameter protocol with 9 s duration was compared with the two-parameter method, as well as the saturated DAM (SDAM) method, the dual refocusing echo acquisition mode (DREAM) method, and the actual flip-angle imaging (AFI) method, for B1 mapping of brain, breast, and abdomen with different orientations and shim settings at 3T. RESULTS: The 3D RF-prepared three-parameter method with complex-subtraction delivered consistently lower RMS error, error mean, error standard deviation, and higher concordance correlation coefficients values than the two-parameter method, the three-parameter method with magnitude-subtraction, the multi-slice DREAM and the 3D AFI, and were close to the results of 2D or multi-slice SDAM. CONCLUSION: The proposed ultrafast 3D RF-prepared three-parameter method with complex-subtraction was demonstrated with high accuracy for B1 mapping of brain, breast, and abdomen.

An approach to evaluation of the point-spread function for 23 Na magnetic resonance imaging.

Despite the technical challenges that require lengthy acquisitions to overcome poor signal-to-noise ratio (SNR), sodium (23 Na) magnetic resonance imaging (MRI) is an intriguing area of research due to its essential role in human metabolism. Low SNR images can impact the measurement of the point-spread function (PSF) by adding uncertainty into the resulting quantities. Here, we present methods to calculate the PSF by using the modulation transfer function (MTF), and a 3D-printed line-pair phantom in the context of 23 Na MRI. A simulation study investigated the effect of noise on the resulting MTF curves, which were derived by direct modulation (DM) and a method utilizing Fourier harmonics (FHs). Experimental data utilized a line-pair phantom with nine spatial frequencies, filled with different concentrations (15, 30, and 60 mM) of sodium in 3% agar. MTF curves were calculated using both methods from data acquired from density-adapted 3D radial projections (DA-3DRP) and Fermat looped orthogonally encoded trajectories (FLORET). Simulations indicated that the DM method increased variability in the MTF curves at all tested noise levels over the FH method. For the experimental data, the FH method resulted in PSFs with a narrower full width half maximum with reduced variability, although the improvement in variability was not as pronounced as predicted by simulations. The DA-3DRP data indicated an improvement in the PSF over FLORET. It was concluded that a 3D-printed line-pair phantom represents a convenient method to measure the PSF experimentally. The MTFs from the noisy images in 23 Na MRI have reduced variability from a FH method over DM.

Development and Testing of a Compact Autorefractor Based on Double-Pass Imaging.

Autorefraction is an objective way to determine the refractive error of the eye, without the need for feedback by the patient or a well-educated practitioner. To make refractive measurements more accessible in the background of the growing prevalence of myopia, a compact autorefractor was built, containing only few optical components and relying on double-pass imaging and the physical properties of the point-spread function and digital image processing instead. A method was developed to analyze spherical defocus as well as the defocus and angle of astigmatism. The device was tested using calibrator eye models in a range of ± 15 D spherical defocus and -3 D astigmatic defocus. Reliable results could be achieved across the whole measurement range, with only a small increase in deviation toward high values of refractive errors, showing the feasibility of a PSF-based approach for a compact and low-cost solution for objective measurements of refractive error.