Deterioration Of Spatial Resolution Research Articles

Improving BFS measurement accuracy of BOTDR based on Cauchy proximal splitting

A novel approach based on the Cauchy proximal splitting (CPS) algorithm is proposed to improve Brillouin frequency shift (BFS) measurement accuracy in Brillouin optical time domain reflectometry system. The CPS algorithm utilizes proximal splitting to handle the data and the penalty function based on Cauchy distribution to accurately estimate the target signal to promote sparsity, achieving significant improvement in signal-to-noise ratio (SNR). Experimental results confirm that with a SNR increase of 12.7 dB, an increase in BFS measurement accuracy from 4.78 MHz to 0.43 MHz is achieved over a 10.3 km sensing fiber. The denoising effects of the CPS, wavelet denoising (WD) and non-local mean (NLM) algorithms are further compared, demonstrating that the CPS algorithm has the lowest root mean square error (0.43 MHz) and no deterioration in spatial resolution rather than the WD and NLM algorithms does.

SNR Enhancement for BOTDR With Spatial-Adaptive Image Denoising Method

A spatial-adaptive image denoising (SAID) method is proposed to enhance the signal-to-noise ratio (SNR) of Brillouin optical time domain reflectometer (BOTDR) without deterioration of spatial resolution. Through analyzing the principle of denoising, the spatial-adaptive denoising network structure is constructed, which can effectively reduce noise and avoid over-smoothing. Moreover, a high-similarity dataset generation method is designed to further enhance the denoising effect. The SAID method is experimentally implemented on two-dimension Brillouin gain spectrum matrix over a 25.1 km-long optical fiber with the spatial resolution of 2 m. The experimental results show that the SNR enhancement of SAID method is 21.92 dB, and the data processing time is only 2.48 s. Whereas the SNR enhancement of conventional 10000 times trace averaging method is merely 9.98 dB, but the data processing time is increased to 174.52 s. Therefore, it is demonstrated that the SAID method has obvious advantages in SNR enhancement and data processing speed without deteriorating the spatial resolution of BOTDR.

Frame rate effects and their compensation on super-resolution microvessel imaging using ultrasound localization microscopy

Ultrasound localization microscopy (ULM) breaks the diffraction limit and allows imaging microvasculature at micrometric resolution while preserving the penetration depth. Frame rate plays an important role for high-quality ULM imaging, but there is still a lack of review and investigation of the frame rate effects on ULM. This work aims to clarify how frame rate influences the performance of ULM, including the effects of microbubble detection, localization and tracking. The performance of ULM was evaluated using an in vivo rat brain dataset (15.6 MHz, 3 tilted plane waves (−5°, 0°, +5°), at a compounded frame rate of 1000 Hz) with different frame rates. Quantification methods, including Fourier ring correlation and saturation parameter, were applied to analyze the spatial resolution and reconstruction efficiency, respectively. In addition, effects on each crucial step in ULM processing were further analyzed. Results showed that when frame rates dropped from 1000 Hz to 250 Hz, the spatial resolution deteriorated from 9.9 μm to 15.0 μm. Applying a velocity constraint was able to improve the ULM performance, but inappropriate constraint may artificially result in high apparent resolution. For the dataset, compared with the results of 1000 Hz frame rate, the velocity was underestimated at 100 Hz with 47.18% difference and the saturation was reduced from 55.00% at 1000 Hz to 43.34% at 100 Hz. Analysis showed that inadequate frame rate generated unreliable microbubble detection, localization and tracking as well as incomplete track reconstruction, resulting in the deterioration in spatial resolution, the underestimation in velocity measurement and the decrease in saturation. Finally, a guidance of determining the frame rate requirement was discussed by considering the required spatial sampling points based on vessel morphology, clutter filtering method, tracking algorithm and acquisition time, which provides indications for future clinical application of ULM method.

Self‐Organizing Pixelated Cs4PbBr6 Scintillator Plate for Large‐Area, Ultra‐Flexible, High Spatial Resolution and Stable X‐Ray Imaging

AbstractNowadays, high performance (stability, spatial resolution, and optical yield) and multi‐functional application (low‐cost, large‐area, and flexible) are urgently needed for X‐ray detectors in national defense and medical treatment et al. Herein, self‐organizing pixelated zero‐dimensional metal halide Cs4PbBr6 based micro‐disks for low‐cost (0.0238 $ cm−2, 1/37 of CsI(Tl)), large‐area and ultra‐flexible scintillator plates are designed, prepared and applied. The theoretical model describes that the micro‐disks‐based structure being separated from others by air can reduce the transverse optical diffusion within the scintillator, especially when the optical boundary of “pixel” surface is changed by metal coating. Meanwhile, such structure also inhibits the stress generation in the crystal when bent. Further characterization points out that the fabricated scintillator plate possesses high spatial resolution (≈15.9 lp mm−1) and light yield (≈19000 ph Me V−1). Especially, the device shows excellent stability and almost no deterioration of spatial resolution after aging in various extreme environments and in extreme bending tests (folding, keeping bending for a long time). Finally, the good suitability to couple with various photoelectric devices and successful imaging demonstrations of nondestructive measurement are exhibited. It is believed that these findings provide a low‐cost and flexible scintillator preparation scheme and demonstrate a pre‐eminent design paradigm.

Non-blind deconvolution with an alternating direction method of multipliers (ADMM) after noise reduction in nondestructive testing

To ensure the quality of material, nondestructive testing is necessary, and radiography testing is the nondestructive technique most commonly used today. For inspection, the quality of a radiographic image is critical, and there are many image artifacts that can reduce inspection accuracies such as noise or blurring. The deterioration in spatial resolution caused by blur in both the X-ray imaging itself and the noise reduction process are particular problems. To tackle them, we implemented a non-blind deconvolution method that employs the alternating direction method of multipliers (ADMM) after noise reduction. Experimental results confirm that the proposed algorithm effectively restores edge sharpness. The 50% modulation transfer function of the restored image of a slit-camera was about 3.54 line-pairs per mm, which is about 2.5 times higher than that of the denoised image. Moreover, the edge preservation index values are about 0.82, 0.54, and 0.75 for the restored, denoised, and acquired images, respectively. Consequentially, the proposed method has the potential to increase inspection efficiency in industrial applications.

High-speed dual-beam, crossed line-scanning fluorescence microscope with a point confocal resolution

Line-scanning microscopes are often used to overcome the limited scanning speed of conventional point-scanning confocal microscopes, at the cost, however, of spatial resolution. In this paper, we present a dual-beam fluorescence line-scanning microscope that can restore the original confocal resolution. This microscope forms two orthogonal line foci in the object plane with perpendicular scanning directions, which create two line-scan images of the same area. From these images, the real noise and confocal characteristics are analyzed. Based on this information, we developed an image restoration algorithm to produce a final image with spatial resolution comparable to that of a conventional point-scanning confocal microscope. This algorithm was derived with the total variation regularization, and the critical image restoration factor for the algorithm was determined via an iterative process. Our results indicate that the intrinsic resolution limit of line-scanning microscopes can be overcome without subsequent deterioration in spatial resolution.

Principal component analysis enhances SNR for dynamic electron paramagnetic resonance oxygen imaging of cycling hypoxia in vivo

Low oxygen concentration (hypoxia) in tumors strongly affects their malignant state and resistance to therapy. These effects may be more deleterious in regions undergoing cycling hypoxia. Electron paramagnetic resonance imaging (EPRI) has provided a noninvasive, quantitative imaging modality to investigate static pO2 in vivo. However, to image changing hypoxia, EPRI images with better temporal resolution may be required. The tradeoff between temporal resolution and signal-to-noise ratio (SNR) results in lower SNR for EPRI images with imaging time short enough to resolve cycling hypoxia. Principal component analysis allows for accelerated image acquisition with acceptable SNR by filtering noise in projection data, from which pO2 images are reconstructed. Principal component analysis is used as a denoising technique by including only low-order components to approximate the EPRI projection data. Simulated and experimental studies show that principal component analysis filtering increases SNR, particularly for small numbers of sub-volumes with changing pO2 , enabling an order of magnitude increase in temporal resolution with minimal deterioration in spatial resolution or image quality. The SNR necessary for dynamic EPRI studies with temporal resolution required to investigate cycling hypoxia and its physiological implications is enabled by principal component analysis filtering.

The motivations and methodology for high-throughput PET imaging of small animals in cancer research

Over the last decade, small-animal PET imaging has become a vital platform technology in cancer research. With the development of molecularly targeted therapies and drug combinations requiring evaluation of different schedules, the number of animals to be imaged within a PET experiment has increased. This paper describes experimental design requirements to reach statistical significance, based on the expected change in tracer uptake in treated animals as compared to the control group, the number of groups that will be imaged, and the expected intra-animal variability for a given tracer. We also review how high-throughput studies can be performed in dedicated small-animal PET, high-resolution clinical PET systems and planar positron imaging systems by imaging more than one animal simultaneously. Customized beds designed to image more than one animal in large-bore small-animal PET scanners are described. Physics issues related to the presence of several rodents within the field of view (i.e. deterioration of spatial resolution and sensitivity as the radial and the axial offsets increase, respectively, as well as a larger effect of attenuation and the number of scatter events), which can be assessed by using the NEMA NU 4 image quality phantom, are detailed.

TH-E-220-02: Spatial Resolution of Proton Tomography: Methods, Initial Phase Space and Object Thickness

Purpose: Protonradiography and tomography was investigated in the early 1970s because of its low radiation dose, high density resolution and ability to image directly protonstopping power.Spatial resolution is still a limiting factor. therefore experimental methods and image reconstruction should be optimized to improve position resolution. Methods: Spatial resolution of protontomography is given by multiple scattering(MCS) of the protons. We employ an improved MCS model to study the impact of proton tomographic set‐ups on spatial resolution, such as different combinations of entrance and exit coordinate and angle measurements, respectively, particle energy and angular confusion of the proton field. Results: It was found that best spatial resolution is obtained by measuring in addition to the entrance and exit coordinates the entrance and exit angles. By applying partial backprojection and a perfect proton fan beam a sufficient spatial resolution can be achieved with less experimental complexity. It was also shown that it is essential to use the most probable proton trajectory to improve spatial resolution. A simple straight line connection for image reconstruction results in a spatial resolution which is not clinically sufficient. The percentage deterioration of spatial resolution due to the angular confusion of the incident proton field is less than the phase space in mrad. Conclusions: Clinically sufficient spatial resolution can be either achieved with a full measurement of entrance and exit coordinates and angles, but also by using a fan beam with small angular confusion and an exit angle measurement. It is necessary to use the most probable proton path for image reconstruction. A simple straight line connection is in general not sufficient. Increasing proton energy improves spatial resolution of an object of constant size. This should be considered in the design of proton therapy facilities.

Zero-filling Technique in Fresnel Transfrom Image Reconstruction for MR Image Denoising

The Fresnel transform imaging method with a nonlinear field gradient for phase encoding has a great property that it can diffuse the noise contained in nuclear magnetic resonance (NMR) signal. But we cannot find any diffuseness of the noise, when we fix the signal matrix size to reconstruct images. However, if we prepare suitable area for the noise diffusing by zero-filling technique before reconstructing images in this method, the spectrum of noise will evenly distribute over all the zero filled area, on the other hand, we can obtain a multi-resolution type image, because the image frequency is split into equal intervals. After removing the noise by a threshold filter in the multi-resolution space, returning the denoised signal to beginning space by taking a series of inverseprocesses and reconstructing it with usual Fresnel transform imaging method, we can obtain an MR image that the noise is greatly improved, whereas the deterioration in spatial resolution is hardly caused.

The robustness of communication of emotion via facial expression: Emotion recognition from photographs with deteriorated pictorial quality

AbstractThis studyThe studies reported here were conducted within the TELEMED project which is funded by the European Community within the RACE program. examines whether the recognition of emotion from facial expressions is impaired by deterioration of spatial resolution, contrast resolution, and picture size. Eighty judges rated 65 stimuli under 11 conditions: Undistorted, reduced spatial resolution (three steps), reduced contrast resolution (three steps), reduced picture size (three steps), and a very ‘hard’ condition combining the severest spatial and contrast resolution. Variation in picture quality was achieved by using a digital video recorder. Recognition rate and intensity ratings were not significantly affected by variations in contrast resolution or picture size. The only significant reduction of recognition rate and intensity ratings resulted from reduction in spatial resolution, but only with the largest deterioration in such resolution. Results are discussed with respect to the fundamental importance of facial expressions in interaction and communication, and with respect to applications, such as tele‐conferencing systems.