Single-Shot 3D Imaging Meta-Microscope.

Three-dimensional (3D) imaging enables high-precision and high-resolution axial positioning, which is crucial for biological imaging, semiconductor defect monitoring, and other applications. Conventional implementations rely on bulky optical elements or scanning mechanisms, resulting in low speed and complicated setups. Here, we generate the double-helix (DH) point spread function with an all-dielectric metasurface and thus innovate the 3D imaging microscope (hence dubbed meta-microscope), both in 4f and 2f imaging systems. The 4f-meta-microscope with a numerical aperture of 0.7 achieves an axial localization accuracy below 0.12 µm within a 15.47 µm detection range, while the 2f-DH meta-microscope with a numerical aperture of 0.3 shows a 1.12 µm accuracy within a 227.33 µm range. We also demonstrate single-shot and accurate 3D biological imaging of the mouse kidney tissue and peach anther, providing a comprehensive and efficient approach for 3D bioimaging and other applications through a single-shot 3D meta-microscope.

Point-Spread Function Deformations Unlock 3D Localization Microscopy on Spherical Nanoparticles.

Nanoparticles (NPs) have proven their applicability in biosensing, drug delivery, and photothermal therapy, but their performance depends critically on the distribution and number of functional groups on their surface. When studying surface functionalization using super-resolution microscopy, the NP modifies the fluorophore's point-spread function (PSF). This leads to systematic mislocalizations in conventional analyses employing Gaussian PSFs. Here, we address this shortcoming by deriving the analytical PSF model for a fluorophore near a spherical NP. Its calculation is four orders of magnitude faster than numerical approaches and thus feasible for direct use in localization algorithms. We fit this model to individual 2D images from DNA-PAINT experiments on DNA-coated gold NPs and demonstrate extraction of the 3D positions of functional groups with <5 nm precision, revealing inhomogeneous surface coverage. Our method is exact, fast, accessible, and poised to become the standard in super-resolution imaging of NPs for biosensing and drug delivery applications.

Practical guidelines for cell segmentation models under optical aberrations in microscopy.

Cell segmentation is essential in biomedical research for analyzing cellular morphology and behavior. Deep learning methods, particularly convolutional neural networks (CNNs), have revolutionized cell segmentation by extracting intricate features from images. However, the robustness of these methods under microscope optical aberrations remains a critical challenge. This study evaluates cell image segmentation models under optical aberrations from fluorescence and bright field microscopy. By simulating different types of aberrations, including astigmatism, coma, spherical aberration, trefoil, and mixed aberrations, we conduct a thorough evaluation of various cell instance segmentation models using the DynamicNuclearNet (DNN) and LIVECell datasets, representing fluorescence and bright field microscopy cell datasets, respectively. We train and test several segmentation models, including the Otsu threshold method and Mask R-CNN with different network heads (FPN, C3) and backbones (ResNet, VGG, Swin Transformer), under aberrated conditions. Additionally, we provide usage recommendations for the Cellpose 2.0 Toolbox on complex cell degradation images. The results indicate that the combination of FPN and SwinS demonstrates superior robustness in handling simple cell images affected by minor aberrations. In contrast, Cellpose 2.0 proves effective for complex cell images under similar conditions. Furthermore, we innovatively propose the Point Spread Function Image Label Classification Model (PLCM). This model can quickly and accurately identify aberration types and amplitudes from PSF images, assisting researchers without optical training. Through PLCM, researchers can better apply our proposed cell segmentation guidelines. This study aims to provide guidance for the effective utilization of cell segmentation models in the presence of minor optical aberrations and pave the way for future research directions.

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.

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.

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.

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.

Serum miR-26a level is decreased in cataract patients with glaucoma and related to visual quality.

CLINICAL RELEVANCE: microRNAs have been found to be involved in the progression of a variety of ocular diseases. BACKGROUND: Cataract and glaucoma often coexist, and combined surgery is a common treatment. The aim of this study is to analyse the correlation between miR-26a and visual quality in cataract patients with glaucoma. METHODS: Seventy patients with cataract and glaucoma and 70 healthy volunteers were enrolled and received phacoemulsification and trabeculectomy. The patients were divided into low and high miR-26a expression groups according to miR-26a mean expression. The objective scattering index, strehl ratio, and modulated transfer function cut-off were analysed by optical quality analysis system II. The changes of miR-26a, objective scattering index, strehl ratio, modulated transfer function cut-off, and the correlation between the indicators were analysed. The downstream genes of miR-26a were analysed by Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes functional enrichment. RESULTS: There were significant differences between patients and controls in lipid biomarker levels and visual indicators. miR-26a was decreased in the patient group. Strehl ratio and modulated transfer function cut-off in the miR-26a low-expression group were lower than in high-expression group, while mean defect of the visual field and objective scattering index were higher than in high-expression group. The miR-26a expression was negatively correlated with the severity of disease and objective scattering index, and positively correlated with strehl ratio and modulated transfer function cut-off. After surgery, miR-26a, strehl ratio, and modulated transfer function cut-off were increased, and objective scattering index was decreased. The downstream genes of miR-26a were related to several biological processes and signalling pathways. CONCLUSION: In cataract patients with glaucoma, miR-26a expression was lower than matched controls and increased following combined cataract removal and trabeculectomy.

Color Flow Ultrasound Spatial Sampling Beam Density for Partial Volume-Corrected Three-Dimensional Volume Flow (3DVF): Theory, Simulation, and Experiment.

OBJECTIVE: The purpose of this study was to quantify the accuracy of partial volume-corrected three-dimensional volume flow (3DVF) measurements as a function of spatial sampling beam density using carefully-designed parametric analyses in order to inform the target applications of 3DVF. METHODS: Experimental investigations employed a mechanically-swept curvilinear ultrasound array to acquire 3D color flow (6.3 MHz) images in flow phantoms consisting of four lumen diameters (6.35, 4.88, 3.18 and 1.65 mm) with volume flow rates of 440, 260, 110 and 30 mL/min, respectively. Partial volume-corrected three-dimensional volume flow (3DVF) measurements, based on the Gaussian surface integration principle, were computed at five regions of interest positioned between depths of 2 and 6 cm in 1 cm increments. At each depth, the color flow beam point spread function (PSF) was also determined, using in-phase/quadrature data, such that 3DVF bias could then be related to spatial sampling beam density. Corresponding simulations were performed for a laminar parabolic flow profile that was sampled using the experimentally-measured PSFs. Volume flow was computed for all combinations of lumen diameters and the PSFs at each depth. RESULTS: Accurate 3DVF measurements, i.e., bias less than ±20%, were achieved for spatial sampling beam densities where at least 6 elevational color flow beams could be positioned across the lumen. In these cases, greater than 8 lateral color flow beams were present. PSF measurements showed an average lateral-to-elevational beam width asymmetry of 1:2. Volume flow measurement bias increased as the color flow beam spatial sampling density within the lumen decreased. CONCLUSION: Applications of 3DVF, particularly those in the clinical domain, should focus on areas where a spatial sampling density of 6 × 6 (lateral x elevational) beams can be realized in order to minimize measurement bias. Matrix-based ultrasound arrays that possess symmetric PSFs may be advantageous to achieve adequate beam densities in smaller vessels.

Framework for evaluating photon-counting detectors under pile-up conditions.

Purpose: While X-ray photon-counting detectors (PCDs) promise to revolutionize medical imaging, theoretical frameworks to evaluate them are commonly limited to incident fluence rates sufficiently low that the detector response can be considered linear. However, typical clinical operating conditions lead to a significant level of pile-up, invalidating this assumption of a linear response. Here, we present a framework that aims to evaluate PCDs, taking into account their non-linear behavior. Approach: We employ small-signal analysis to study the behavior of PCDs under pile-up conditions. The response is approximated as linear around a given operating point, determined by the incident spectrum and fluence rate. The detector response is subsequently described by the proposed perturbation point spread function (pPSF). We demonstrate this approach using Monte-Carlo simulations of idealized direct- and indirect-conversion PCDs. Results: The pPSFs of two PCDs are calculated. It is then shown how the pPSF allows to determine the sensitivity of the detector signal to an arbitrary lesion. This example illustrates the detrimental influence of pile-up, which may cause non-intuitive effects such as contrast/contrast-to-noise ratio inversion or cancellation between/within energy bins. Conclusions: The proposed framework permits quantifying the spectral and spatial performance of PCDs under clinically realistic conditions at a given operating point. The presented example illustrates why PCDs should not be analyzed assuming that they are linear systems. The framework can, for example, be used to guide the development of PCDs and PCD-based systems. Furthermore, it can be applied to adapt commonly used measures, such as the modulation transfer function, to non-linear PCDs.

Investigation of Deconvolution Method with Adaptive Point Spread Function Based on Scintillator Thickness in Wavelet Domain.

In recent years, indirect digital radiography detectors have been actively studied to improve radiographic image performance with low radiation exposure. This study aimed to achieve low-dose radiation imaging with a thick scintillation detector while simultaneously obtaining the resolution of a thin scintillation detector. The proposed method was used to predict the optimal point spread function (PSF) between thin and thick scintillation detectors by considering image quality assessment (IQA). The process of identifying the optimal PSF was performed on each sub-band in the wavelet domain to improve restoration accuracy. In the experiments, the edge preservation index (EPI) values of the non-blind deblurred image with a blurring sigma of σ = 5.13 pixels and the image obtained with optimal parameters from the thick scintillator using the proposed method were approximately 0.62 and 0.76, respectively. The coefficient of variation (COV) values for the two images were approximately 1.02 and 0.63, respectively. The proposed method was validated through simulations and experimental results, and its viability is expected to be verified on various radiological imaging systems.

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.

Model-based iterative reconstruction for direct imaging with point spread function encoded echo planar MRI.

BACKGROUND: Echo planar imaging (EPI) is a fast measurement technique commonly used in magnetic resonance imaging (MRI), but is highly sensitive to measurement non-idealities in reconstruction. Point spread function (PSF)-encoded EPI is a multi-shot strategy which alleviates distortion, but acquisition of encodings suitable for direct distortion-free imaging prolongs scan time. In this work, a model-based iterative reconstruction (MBIR) framework is introduced for direct imaging with PSF-EPI to improve image quality and acceleration potential. METHODS: An MBIR platform was developed for accelerated PSF-EPI. The reconstruction utilizes a subspace representation, is regularized to promote local low-rankedness (LLR), and uses variable splitting for efficient iteration. Comparisons were made against standard reconstructions from prospectively accelerated PSF-EPI data and with retrospective subsampling. Exploring aggressive partial Fourier acceleration of the PSF-encoding dimension, additional comparisons were made against an extension of Homodyne to direct PSF-EPI in numerical experiments. A neuroradiologists' assessment was completed comparing images reconstructed with MBIR from retrospectively truncated data directly against images obtained with standard reconstructions from non-truncated datasets. RESULTS: Image quality results were consistently superior for MBIR relative to standard and Homodyne reconstructions. As the MBIR signal model and reconstruction allow for arbitrary sampling of the PSF space, random sampling of the PSF-encoding dimension was also demonstrated, with quantitative assessments indicating best performance achieved through nonuniform PSF sampling combined with partial Fourier. With retrospective subsampling, MBIR reconstructs high-quality images from sub-minute scan datasets. MBIR was shown to be superior in a neuroradiologists' assessment with respect to three of five performance criteria, with equivalence for the remaining two. CONCLUSIONS: A novel image reconstruction framework is introduced for direct imaging with PSF-EPI, enabling arbitrary PSF space sampling and reconstruction of diagnostic-quality images from highly accelerated PSF-encoded EPI data.

PSF-Radon transform algorithm: Measurement of the point-spread function from the Radon transform of the line-spread function.

In this article, we present a new method called point spread function (PSF)-Radon transform algorithm. This algorithm consists on recovering the instrument PSF from the Radon transform (in the line direction axis) of the line spread function (i.e., the image of a line). We present the method and tested with synthetic images, and real images from macro lens camera and microscopy. A stand-alone program along with a tutorial is available, for any interested user, in Martinez (PSF-Radon transform algorithm, standalone program). RESEARCH HIGHLIGHTS: Determining the instrument PSF is a key issue. Precise PSF determinations are mandatory if image improvement is performed numerically by deconvolution. Much less exposure time to achieve the same performance than a measurement of the PSF from a very small bead. Does not require having to adjust the PSF by an analytical function to overcome the noise uncertainties.

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.

McSTRA: A multi-branch cascaded swin transformer for point spread function-guided robust MRI reconstruction.

Deep learning MRI reconstruction methods are often based on Convolutional neural network (CNN) models; however, they are limited in capturing global correlations among image features due to the intrinsic locality of the convolution operation. Conversely, the recent vision transformer models (ViT) are capable of capturing global correlations by applying self-attention operations on image patches. Nevertheless, the existing transformer models for MRI reconstruction rarely leverage the physics of MRI. In this paper, we propose a novel physics-based transformer model titled, the Multi-branch Cascaded Swin Transformers (McSTRA) for robust MRI reconstruction. McSTRA combines several interconnected MRI physics-related concepts with the Swin transformers: it exploits global MRI features via the shifted window self-attention mechanism; it extracts MRI features belonging to different spectral components via a multi-branch setup; it iterates between intermediate de-aliasing and data consistency via a cascaded network with intermediate loss computations; furthermore, we propose a point spread function-guided positional embedding generation mechanism for the Swin transformers which exploit the spread of the aliasing artifacts for effective reconstruction. With the combination of all these components, McSTRA outperforms the state-of-the-art methods while demonstrating robustness in adversarial conditions such as higher accelerations, noisy data, different undersampling protocols, out-of-distribution data, and abnormalities in anatomy.

Visualization of small brain nuclei with a high-spatial resolution, clinically available whole-body PET scanner.

OBJECTIVE: To verify the visibility of physiological 18F-fluorodeoxyglucose (18F-FDG) uptake in nuclei in and around the brainstem by a whole-body (WB) silicon photomultiplier positron emission tomography (SiPM-PET) scanner with point-spread function (PSF) reconstruction using various iteration numbers. METHODS: Ten healthy subjects (5 men, 5 women; mean age, 56.0 ± 5.0 years) who underwent 18F-FDG PET/CT using a WB SiPM-PET scanner and magnetic resonance imaging (MRI) of the brain including a spin-echo three-dimensional sampling perfection with application-optimized contrasts using different flip angle evolutions fluid-attenuated inversion recovery (3D-FLAIR) and a 3D-T1 magnetization-prepared rapid gradient-echo (T1-MPRAGE) images were enrolled. Each acquired PET image was reconstructed using ordered-subset expectation maximization (OSEM) with iteration numbers of 4, 16, 64, and 256 (subset 5 fixed) + time-of-flight (TOF) + PSF. The reconstructed PET images and 3D-FLAIR images for each subject were registered to individual T1-MPRAGE volumes using normalized mutual information criteria. For each MR-coregistered individual PET image, the pattern of FDG uptake in the inferior olivary nuclei (ION), dentate nuclei (DN), midbrain raphe nuclei (MRN), inferior colliculi (IC), mammillary bodies (MB), red nuclei (RN), subthalamic nuclei (STN), lateral geniculate nuclei (LGN), medial geniculate nuclei (MGN), and superior colliculi (SC) was visually classified into the following three categories: good, clearly distinguishable FDG accumulation; fair, obscure contour of FDG accumulation; poor, FDG accumulation indistinguishable from surrounding uptake. RESULTS: Among individual 18F-FDG PET images with OSEM iterations of 4, 16, 64, and 256 + TOF + PSF, the iteration numbers that showed the best visibility in each structure were as follows: ION, MRN, LGN, MGN, and SC, iteration 64; DN, iteration 16; IC, iterations 16, 64, and 256; MB, iterations 64 and 256; and RN and STN, iterations 16 and 64, respectively. Of the four iterations, the 18F-FDG PET image of iteration 64 visualized FDG accumulation in small structures in and around the brainstem most clearly (good, 98 structures; fair, 2 structures). CONCLUSIONS: A clinically available WB SiPM-PET scanner is useful for visualizing physiological FDG uptake in small brain nuclei, using a sufficiently high number of iterations for OSEM with TOF and PSF reconstructions.

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%.

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.

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.