Point Spread Function Of System Research Articles

Optimization of the performance of hand‐held FFOCT scanner

In this work, we have established an improved handheld full-field optical coherence tomography (FFOCT) system based on the tandem structure of Michelson interferometer and Fizeau interferometer. We have analyzed the influence of wave aberrations of the handheld FFOCT as a function of orientation deviation of mirror M2 on the system point spread function (PSF) by using the nodal aberration theory. It is found that the range of the orientation deviation of mirror M2 must be less than 0.1° to generate stable FFOCT images. The effect of wave aberrations of defocus as a result of the refractive index difference on the system PSF has also been calculated, the measuring depth in the case of the sample with refractive index of 1.5 and the propagation medium is air (n = 1) should be less than 20 μm. Theoretical analyses have been demonstrated by the experimental results of aluminum powder, onion and porcine myocardium. By comparing the defocused FFOCT images of aluminum powder with defocused FFOCT images of onion and porcine myocardium, it can be concluded that reducing the refractive index difference between the medium and sample can increase the imaging depth of handheld FFOCT system.

Метод розрахунку функції розсіювання точки оптичної системи

The article presents a mathematical apparatus for precise calculation of the three-dimensional point spread function (PSF) of a high-aperture optical system. The proposed method is based on the Huygens-Fresnel principle: a spherical wave on the three-dimensional surface of the exit pupil is considered as result of the superposition of elementary secondary point radiation sources. These point sources emit coherent electromagnetic waves with a spherical wave front. They form a certain distribution of generalized complex amplitudes in three-dimensional space near the focus point. This distribution is used to calculate the intensity distribution in the focus area of ​​the optical system, which is the PSF. The article presents the results of PSFcalculations and their comparative.

High-fidelity deconvolution for acoustic-resolution photoacoustic microscopy enabled by convolutional neural networks

Acoustic-resolution photoacoustic microscopy (AR-PAM) image resolution is determined by the point spread function (PSF) of the imaging system. Previous algorithms, including Richardson–Lucy (R–L) deconvolution and model-based (MB) deconvolution, improve spatial resolution by taking advantage of the PSF as prior knowledge. However, these methods encounter the problems of inaccurate deconvolution, meaning the deconvolved feature size and the original one are not consistent (e.g., the former can be smaller than the latter). We present a novel deep convolution neural network (CNN)-based algorithm featuring high-fidelity recovery of multiscale feature size to improve lateral resolution of AR-PAM. The CNN is trained with simulated image pairs of line patterns, which is to mimic blood vessels. To investigate the suitable CNN model structure and elaborate on the effectiveness of CNN methods compared with non-learning methods, we select five different CNN models, while R–L and directional MB methods are also applied for comparison. Besides simulated data, experimental data including tungsten wires, leaf veins, and in vivo blood vessels are also evaluated. A custom-defined metric of relative size error (RSE) is used to quantify the multiscale feature recovery ability of different methods. Compared to other methods, enhanced deep super resolution (EDSR) network and residual in residual dense block network (RRDBNet) model show better recovery in terms of RSE for tungsten wires with diameters ranging from 30 μm to 120 μm. Moreover, AR-PAM images of leaf veins are tested to demonstrate the effectiveness of the optimized CNN methods (by EDSR and RRDBNet) for complex patterns. Finally, in vivo images of mouse ear blood vessels and rat ear blood vessels are acquired and then deconvolved, and the results show that the proposed CNN method (notably RRDBNet) enables accurate deconvolution of multiscale feature size and thus good fidelity.

A Novel Approach for the Detection of Every Significant Collapsing Bubble in Passive Cavitation Imaging.

Passive cavitation image (PCI) shows the power distribution of the acoustic emissions resulting from cavitation bubble collapses. The conventional PCI convolves the emitted cavitation signals with the point spread function of an imaging system, and it suffers from a low spatial resolution and contrast due to the increased sidelobe artifacts accumulated during the temporal integral process. To overcome the problems, the present study considers a 3-D time history of instantaneous PCIs where cavitation occurs at the local maxima of the main lobes of the beamformed cavitation field surrounded by the sidelobes largely spreading out in a time-space domain. A spatial and temporal gating technique was employed to detect the local maxima so that cavitation bubbles can be identified with their collapsing strength. The proposed approach was verified by the simulation for single and multiple cavitation bubbles, proving that it accurately detects the location and strength of the collapsing bubbles. An experimental test was also carried out for the cavitation bubbles produced by a clinical extracorporeal shock wave therapeutic device, which underpins that the proposed method successfully identifies every individual cavitation bubble.

Examination of deblur processing according to optical parameters in aerial image

We propose a pre-processing method of source image to reduce blur of aerial image that is formed with aerial imaging by retro-reflection (AIRR). The image blur in the AIRR optical system depends on the optical elements and the incident angle. In this paper, the point spread function (PSF) was measured by changing the optical arrangements and the retro-reflectors. A deconvolution processing based on the obtained PSF was applied on the aerial image. The accuracy of the deconvolution processing was quantitatively evaluated by use of three types of image quality indices. These numerical experimental results show the possibility of removing the blur of the aerial image by applying the deconvolution process based on the PSF of AIRR optical system.

Light sheet based volume flow cytometry (VFC) for rapid volume reconstruction and parameter estimation on the go

Optical imaging is paramount for disease diagnosis and to access its progression over time. The proposed optical flow imaging (VFC/iLIFE) is a powerful technique that adds new capabilities (3D volume visualization, organelle-level resolution, and multi-organelle screening) to the existing system. Unlike state-of-the-art point-illumination-based biomedical imaging techniques, the sheet-based VFC technique is capable of single-shot sectional visualization, high throughput interrogation, real-time parameter estimation, and instant volume reconstruction with organelle-level resolution of live specimens. The specimen flow system was realized on a multichannel (Y-type) microfluidic chip that enables visualization of organelle distribution in several cells in-parallel at a relatively high flow-rate (2000 nl/min). The calibration of VFC system requires the study of point emitters (fluorescent beads) at physiologically relevant flow-rates (500–2000 nl/min) for determining flow-induced optical aberration in the system point spread function (PSF). Subsequently, the recorded raw images and volumes were computationally deconvolved with flow-variant PSF to reconstruct the cell volume. High throughput investigation of the mitochondrial network in HeLa cancer cell was carried out at sub-cellular resolution in real-time and critical parameters (mitochondria count and size distribution, morphology, entropy, and cell strain statistics) were determined on-the-go. These parameters determine the physiological state of cells, and the changes over-time, revealing the metastatic progression of diseases. Overall, the developed VFC system enables real-time monitoring of sub-cellular organelle organization at a high-throughput with high-content capacity.

Adaptive kernel regression and energy concentration criterion for infrared dim small target detection

It is always a challenging task to detect a small target with low signal-to-noise ratio under complex background in infrared images. To address this problem, an effective algorithm based on background subtraction is proposed. First, we add the gradient feature into the kernel regression model to acquire an edge-preserving background estimation. The smoothing matrix of the kernel function is reestablished by a rotation angle and an elongation scale. Further, a multiscale first-order directional derivative filter is presented to calculate these factors adaptively. Second, to segment the real target from the subtracted image, we model the imaging process of the small target using the point spread function of the optical system. According to the analysis of the imaging size and the energy distribution of target, an energy concentration criterion is constructed and used for target extraction. Finally, comparison of experimental results demonstrates that the proposed algorithm achieves robust performances on background suppression and extracts the target accurately with a high detection probability and low false alarm rate.

Improving image contrast and accuracy in velocity estimation by convolution filters for intracardiac blood flow imaging

In this study, the point spread function (PSF) of an ultrasound imaging system was estimated and used as a reference signal in a filtering method for improvement of image quality. The PSF of the imaging system was estimated from measured echo signals from an imaging target. Convolution filters (including deconvolution) were used for improvement of image contrast and spatial resolution. Furthermore, the accuracy in estimation of velocity vectors was evaluated for investigation of the impact of the proposed filters on velocity estimation. In the phantom experiment, contrast of the B-mode image was improved from 76.4 dB to 81.1 dB and 77.8 dB using the convolution and deconvolution filters, respectively. Also, the two-dimensional (2D) velocity distribution in the phantom was estimated by the block matching method, and the bias error (BE) in the estimated lateral velocity was reduced from −19.7% to 2.16% and 2.29% using the convolution and the deconvolution filters, respectively.

Image restoration for real-world under-display imaging.

Under-display imaging technique was recently proposed to enlarge the screen-to-body ratio for full-screen devices. However, existing image restoration algorithms have difficulty generalizing to real-world under-display (UD) images, especially to images containing strong light sources. To address this issue, we propose a novel method for building a synthetic dataset (CalibPSF dataset) and introduce a two-stage neural network to solve the under-display imaging degradation problem. The CalibPSF dataset is generated using the calibrated high dynamic range point spread function (PSF) of the under-display optical system and contains various simulated light sources. The two-stage network solves the color distortion and diffraction degradation in order. We evaluate the performance of our algorithm on our captured real-world test set. Comprehensive experiments demonstrate the superiority of our method in different dynamic range scenes.

Polarization-sensitive imaging based on incoherent holography.

The polarization-sensitive imaging technology is proposed based on incoherent holography. The distribution of state of polarization (SoP) of the object light field can be reconstructed by measuring the phase difference and amplitude ratio of two components of the Jones vector on the basis of incoherent self-interference theory and the accurate point spread function (PSF) of the incoherent holographic system. In the analysis of Fresnel diffraction, we develop a new method to greatly simplify the calculation of the accurate PSF by means of imaging property of lens and symbolic mathematics tools. In the recording process, we utilize the automation of phase shift, photography, and synthesization of color hologram to greatly shorten the total recording time of a group of phase-shifted holograms. The experimental results show that the proposed technology can accurately realize polarization-sensitive imaging and it is much simpler for complete linearly polarized light.

Motion artifacts assessment and correction using optical tracking in synchrotron radiation breast CT.

PurposeThe SYRMA‐3D collaboration is setting up a breast computed tomography (bCT) clinical program at the Elettra synchrotron radiation facility in Trieste, Italy. Unlike the few dedicated scanners available at hospitals, synchrotron radiation bCT requires the patient's rotation, which in turn implies a long scan duration (from tens of seconds to few minutes). At the same time, it allows the achievement of high spatial resolution. These features make synchrotron radiation bCT prone to motion artifacts. This article aims at assessing and compensating for motion artifacts through an optical tracking approach.MethodsIn this study, patients’ movements due to breathing have been first assessed on seven volunteers and then simulated during the CT scans of a breast phantom and a surgical specimen, by adding a periodic oscillatory motion (constant speed, 1 mm amplitude, 12 cycles/minute). CT scans were carried out at 28 keV with a mean glandular dose of 5 mGy. Motion artifacts were evaluated and a correction algorithm based on the optical tracking of fiducial marks was introduced. A quantitative analysis based on the structural similarity (SSIM) index and the normalized mean square error (nMSE) was performed on the reconstructed CT images.ResultsCT images reconstructed through the optical tracking procedure were found to be as good as the motionless reference image. Moreover, the analysis of SSIM and nMSE demonstrated that an uncorrected motion of the order of the system's point spread function (around 0.1 mm in the present case) can be tolerated.ConclusionsResults suggest that a motion correction procedure based on an optical tracking system would be beneficial in synchrotron radiation bCT.

Calculation of ensquared energy of the diffraction-limited optical system with Higher-order parabolic filter

Mathematical properties of the ensquared energy functions for apodized point-spread function (PSF) are presented. An expression of ensquared energy for the apodized point Spread function of the optical system with a circular aperture was derived using a parabolic apodized filter with a different arrangement N =1, 2,3,4. The results obtained were discussed graphically.

A light field measurement system through PSF estimation by a morphology-based method

Light field imaging technology can obtain three-dimensional (3D) information of a test surface in a single exposure. Traditional light field reconstruction algorithms not only take a long time to trace back to the original image, but also require the exact parameters of the light field system, such as the position and posture of a microlens array (MLA), which will cause errors in the reconstructed image if these parameters cannot be precisely obtained. This paper proposes a reconstruction algorithm for light field imaging based on the point spread function (PSF), which does not require prior knowledge of the system. The accurate PSF derivation process of a light field system is presented, and modeling and simulation were conducted to obtain the relationship between the spatial distribution characteristics and the PSF of the light field system. A morphology-based method is proposed to analyze the overlapping area of the subimages of light field images to identify the accurate spatial location of the MLA used in the system, which is thereafter used to accurately refocus light field imaging. A light field system is built to verify the algorithm’s effectiveness. Experimental results show that the measurement accuracy is increased over 41.0% compared with the traditional method by measuring a step standard. The accuracy of parameters is also improved through a microstructure measurement with a peak-to-valley value of 25.4% and root mean square value of 23.5% improvement. This further validates that the algorithm can effectively improve the refocusing efficiency and the accuracy of the light field imaging results with the superiority of refocusing light field imaging without prior knowledge of the system. The proposed method provides a new solution for fast and accurate 3D measurement based on a light field.

Optical Aberration Calibration and Correction of Photographic System Based on Wavefront Coding.

The image deconvolution technique can recover potential sharp images from blurred images affected by aberrations. Obtaining the point spread function (PSF) of the imaging system accurately is a prerequisite for robust deconvolution. In this paper, a computational imaging method based on wavefront coding is proposed to reconstruct the wavefront aberration of a photographic system. Firstly, a group of images affected by local aberration is obtained by applying wavefront coding on the optical system’s spectral plane. Then, the PSF is recovered accurately by pupil function synthesis, and finally, the aberration-affected images are recovered by image deconvolution. After aberration correction, the image’s coefficient of variation and mean relative deviation are improved by 60% and 30%, respectively, and the image can reach the limit of resolution of the sensor, as proved by the resolution test board. Meanwhile, the method’s robust anti-noise capability is confirmed through simulation experiments. Through the conversion of the complexity of optical design to a post-processing algorithm, this method offers an economical and efficient strategy for obtaining high-resolution and high-quality images using a simple large-field lens.

Photoacoustic Tomography Image Restoration With Measured Spatially Variant Point Spread Functions.

The spatial resolution of photoacoustic tomography (PAT) can be characterized by the point spread function (PSF) of the imaging system. Due to the tomographic detection geometry, the PAT image degradation model could be generally described by using spatially variant PSFs. Deconvolution of the PAT image with these PSFs could restore image resolution and recover object details. Previous PAT image restoration algorithms assume that the degraded images can be restored by either a single uniform PSF, or some blind estimation of the spatially variant PSFs. In this work, we propose a PAT image restoration method to improve image quality and resolution based on experimentally measured spatially variant PSFs. Using photoacoustic absorbing microspheres, we design a rigorous PSF measurement procedure, and successfully acquire a dense set of spatially variant PSFs for a commercial cross-sectional PAT system. A pixel-wise PSF map is further obtained by employing a multi-Gaussian-based fitting and interpolation algorithm. To perform image restoration, an optimization-based iterative restoration model with two kinds of regularizations is proposed. We perform phantom and in vivo mice imaging experiments to verify the proposed method, and the results show significant image quality and resolution improvement.

Iterative-Trained Semi-Blind Deconvolution Algorithm to Compensate Straylight in Retinal Images.

The optical quality of an image depends on both the optical properties of the imaging system and the physical properties of the medium in which the light travels from the object to the final imaging sensor. The analysis of the point spread function of the optical system is an objective way to quantify the image degradation. In retinal imaging, the presence of corneal or cristalline lens opacifications spread the light at wide angular distributions. If the mathematical operator that degrades the image is known, the image can be restored through deconvolution methods. In the particular case of retinal imaging, this operator may be unknown (or partially) due to the presence of cataracts, corneal edema, or vitreous opacification. In those cases, blind deconvolution theory provides useful results to restore important spatial information of the image. In this work, a new semi-blind deconvolution method has been developed by training an iterative process with the Glare Spread Function kernel based on the Richardson-Lucy deconvolution algorithm to compensate a veiling glare effect in retinal images due to intraocular straylight. The method was first tested with simulated retinal images generated from a straylight eye model and applied to a real retinal image dataset composed of healthy subjects and patients with glaucoma and diabetic retinopathy. Results showed the capacity of the algorithm to detect and compensate the veiling glare degradation and improving the image sharpness up to 1000% in the case of healthy subjects and up to 700% in the pathological retinal images. This image quality improvement allows performing image segmentation processing with restored hidden spatial information after deconvolution.

Full-field quantum imaging with a single-photon avalanche diode camera

Single-photon-avalanche diode (SPAD) arrays are essential tools in biophotonics, optical ranging and sensing and quantum optics. However, their small number of pixels, low quantum efficiency and small fill factor have so far hindered their use for practical imaging applications. Here, we demonstrate full-field entangled photon pair correlation imaging using a 100-kpixels SPAD camera. By measuring photon coincidences between more than 500 million pairs of positions, we retrieve the full point spread function of the imaging system and subsequently high-resolution images of target objects illuminated by spatially entangled photon pairs. We show that our imaging approach is robust against stray light, enabling quantum imaging technologies to move beyond laboratory experiments towards real-world applications such as quantum LiDAR.

Explicit calculation of Point Spread Function of optical system

The paper presents novel formulas for an explicit calculation of the Point Spread Function for an optical system with a circular pupil and the case of axial-point imaging, which were derived with the use of Sonin’s integral. In such a case, it is not needed to perform integration in the pupil, as it is usual with different methods. The approach is presented and verified with examples. The presented apparatus wide-spreads the theory of calculation of the Point Spread Function, and one can use it as an alternative solution of the mentioned task.

Lensless ghost imaging with hollow-Gaussian modulated incoherent sources in atmospheric turbulence

Lensless ghost imaging (LGI) with hollow-Gaussian modulated incoherent sources through atmospheric turbulence is investigated theoretically. The analytical formula for the point spread function of the LGI system with the hollow-Gaussian source through atmospheric turbulence is derived. By using the anti-turbulence properties of the hollow-Gaussian source, it is shown that the resolution of LGI under atmospheric turbulence can be obviously improved by properly increasing the beam order of the hollow-Gaussian incoherent source when compared with that by using traditional incoherent source.

Joint Blind Deconvolution and Robust Principal Component Analysis for Blood Flow Estimation in Medical Ultrasound Imaging

This article addresses the problem of high-resolution Doppler blood flow estimation from an ultrafast sequence of ultrasound images. Formulating the separation of clutter and blood components as an inverse problem has been shown in the literature to be a good alternative to spatio-temporal singular value decomposition (SVD)-based clutter filtering. In particular, a deconvolution step has recently been embedded in such a problem to mitigate the influence of the point spread function (PSF) of the imaging system. Deconvolution was shown in this context to improve the accuracy of the blood flow reconstruction. However, the PSF needs to be measured experimentally, and measuring it requires nontrivial experimental setups. To overcome this limitation, we propose herein a blind deconvolution method able to estimate both the blood component and the PSF from Doppler data. Numerical experiments conducted on simulated and in vivo data demonstrate qualitatively and quantitatively the effectiveness of the proposed approach in comparison with the previous method based on experimentally measured PSF and two other state-of-the-art approaches.