High-resolution Reconstruction Algorithm Research Articles

High-resolution reconstruction-based investigation of multi-scale lamellar microstructures by coupled crystal plasticity and in-situ experiment

This study aims to establish a novel approach to better understand and predict material behavior in multi-scale lamellar microstructures. High-resolution reconstruction is built on collaborative characterization at both grain and sub-grain scale. A framework for microstructural characterization integrates, secondary electron imaging (SEI), electron backscatter diffraction (EBSD), and image recognition, to ensure that the reconstructed microstructure adequately represents the equivalent grain size, lamellar spacing, and lamellar geometric orientation. Importantly, a high-resolution reconstruction algorithm was developed combining the Laguerre-Voronoi tessellation and minimum bounding sphere (MBS), which allows the reconstructed model retain multi-scale microstructures. Finally, the mechanical properties of pearlite were investigated by combining crystal plasticity simulation with in-situ scanning electron microscopy (SEM) tensile testing based on high-resolution reconstruction. Stress-strain field analysis revealed that cross-lamellae strain bands originate from ferrite large deformation-induced shear transmission, with marked strain distribution heterogeneity within identical lamellae. This concurrently validated the excellent reliability of the novel strategy.

High-resolution reconstruction algorithm for the three-dimensional velocity field produced by atomization of two impinging jets based on deep learning

The velocity fields measured by experiments or determined through simulations are essential in advancing our understanding of the complex atomization process of impinging jets. However, existing methods are expensive and time-consuming. In this study, we apply deep learning to the estimation of the three-dimensional velocity fields produced by the atomization of two impinging jets. Two deep learning models are developed, namely, a liquid volume fraction (LVF) estimation model based on the Swin Transformer architecture and a three-dimensional velocity field estimation model based on four-dimensional convolution (4D-Conv). The dataset for training the models is generated by direct numerical simulations (DNS). To train the LVF model, we utilize two gray images generated by a pinhole camera model, mimicking the acquisition of experimental images. We then introduce a mask generated by binocular vision techniques into the LVF model. The LVF fields estimated with the mask are in better agreement with the reference DNS data. We further utilize the estimated LVF fields to train the 4D-Conv-based model. The mean absolute percentage error compared with the results of a full-flow test is found to be less than 5%. The results indicate that the proposed approach has the potential to accurately reconstruct volume velocity data from two-dimensional images.

Integral Imaging Based Optical Image Encryption Using CA-DNA Algorithm

Under the computational integral imaging-based security system, the application of Deoxyribonucleic Acid (DNA) encoding algorithm will cause silhouettes in the cipher image, thereby reducing the security of the system. To solve this problem, we introduced a cellular automata-based DNA (CA-DNA) algorithm, which effectively hides the distribution information of the original scene. It can prevent attackers from obtaining any valid information based on the statistical characteristics of the image, which makes our encryption system more security. At the same time, an improved high-resolution reconstruction algorithm is applied to achieve a high-quality decrypted scene. We conducted relevant experiments to certificate the effectiveness of proposed method. Experimental results verify that the scheme has high security and robustness.

SU‐E‐I‐14: Avoiding a Common Pitfall in Performing MTF Measurements with High Resolution Kernels

Purpose:The modulation transfer function (MTF) is frequently used to assess high contrast spatial resolution for routine quality assurance in CT imaging. High resolution reconstruction kernels provide new challenges for MTF estimation. The purpose of this work is to demonstrate the effect of CT number saturation on MTF estimation.Methods:A small bead contained in a CATPHAN 600 phantom was imaged at two different slice thicknesses, 2.5 mm and 5.0 mm, on a GE CT 750 HD scanner using an HD Bone Plus reconstruction algorithm in a high resolution scan mode. The resulting images were 2‐D point spread functions (PSF's), which were integrated to create line spread functions, and Fourier transformed to yield MTF's.Results:Using a high resolution reconstruction algorithm and the 2.5 mm slice thickness, it was found that the CT number for several pixels in the PSF reached 3071, the maximum value allowed for this system. Using the same algorithm with the 5.0 mm slice, no pixel values reached the CT number limit. Comparing the two MTF's it was found that the MTF affected by CT number saturation had a 10% cut‐off that was shifted downwards, from 15.6 lp/cm to 14.9 lp/cm. Additionally, the MTF affected by CT number saturation exhibited a spurious lobe beyond the true limiting resolution of the CT scanner.Conclusion:The downwards shift in MTF cut‐off is a subtle but important effect to consider when attempting to measure MTF for routine quality assurance. While a downwards shift in MTF cut‐off is not easily identified, CT number saturation is readily identified in by examining the entire MTF curve and identifying the spurious lobe produced. CT number saturation is an important consideration when examining test objects to be used for MTF estimation when the algorithm being used is high resolution.This work was supported by the AAPM grant for Diagnostic Imaging Residencies

High-definition computed tomography for coronary artery stents imaging: Initial evaluation of the optimal reconstruction algorithm

ObjectiveThe aim of this study was to evaluate the in vivo performance of four image reconstruction algorithms in a high-definition CT (HDCT) scanner with improved spatial resolution for the evaluation of coronary artery stents and intrastent lumina. Materials and methodsThirty-nine consecutive patients with a total of 71 implanted coronary stents underwent coronary CT angiography (CCTA) on a HDCT (Discovery CT 750 HD; GE Healthcare) with the high-resolution scanning mode. Four different reconstruction algorithms (HD-stand, HD-detail; HD-stand-plus; HD-detail-plus) were applied to reconstruct the stented coronary arteries. Image quality for stent characterization was assessed. Image noise and intrastent luminal diameter were measured. The relationship between the measurement of inner stent diameter (ISD) and the true stent diameter (TSD) and stent type were analysed. ResultsThe stent-dedicated kernel (HD-detail) offered the highest percentage (53.5%) of good image quality for stent characterization and the highest ratio (68.0±8.4%) of visible stent lumen/true stent lumen for luminal diameter measurement at the expense of an increased overall image noise. The Pearson correlation coefficient between the ISD and TSD measurement and spearman correlation coefficient between the ISD measurement and stent type were 0.83 and 0.48, respectively. ConclusionsCompared with standard reconstruction algorithms, high-definition CT imaging technique with dedicated high-resolution reconstruction algorithm provides more accurate stent characterization and intrastent luminal diameter measurement.

Edge Detection from Non-Uniform Fourier Data Using the Convolutional Gridding Algorithm

Detecting edges in images from a finite sampling of Fourier data is important in a variety of applications. For example, internal edge information can be used to identify tissue boundaries of the brain in a magnetic resonance imaging (MRI) scan, which is an essential part of clinical diagnosis. Likewise, it can also be used to identify targets from synthetic aperture radar data. Edge information is also critical in determining regions of smoothness so that high resolution reconstruction algorithms, i.e. those that do not smear over the internal boundaries of an image, can be applied. In some applications, such as MRI, the sampling patterns may be designed to oversample the low frequency while more sparsely sampling the high frequency modes. This type of non-uniform sampling creates additional difficulties in processing the image. In particular, there is no fast reconstruction algorithm, since the FFT is not applicable. However, interpolating such highly non-uniform Fourier data to the uniform coefficients (so that the FFT can be employed) may introduce large errors in the high frequency modes, which is especially problematic for edge detection. Convolutional gridding, also referred to as the non-uniform FFT, is a forward method that uses a convolution process to obtain uniform Fourier data so that the FFT can be directly applied to recover the underlying image. Carefully chosen parameters ensure that the algorithm retains accuracy in the high frequency coefficients. Similarly, the convolutional gridding edge detection algorithm developed in this paper provides an efficient and robust way to calculate edges. We demonstrate our technique in one and two dimensional examples.

Redundancy elimination and high resolution algorithm for reconstruction of digital holograms

A fast and high-resolution reconstruction algorithm with variable resolution increasing ratio and down-sampling ratio is proposed. Since the digital holography requires that the space-bandwidth product of the recording system should be greater than that of the object so as to ensure no loss of information, usually much redundant information and pixels exist in the recorded digital hologram. According to that, we propose utilizing a flexible down-sampling process with variable ratio to eliminate the redundancy. The technical characteristics are analyzed. The validity of this method is shown by both calculations based on theory analysis and experimental results.

Reconstruction Algorithms Influence the Follow-Up Variability in the Longitudinal CT Emphysema Index Measurements

ObjectiveWe wanted to compare the variability in the longitudinal emphysema index (EI) measurements that were computed with standard and high resolution (HR) reconstruction algorithms (RAs).Materials and MethodsWe performed a retrospective review of 475 patients who underwent CT for surveillance of lung nodules. From this cohort, 50 patients (28 male) were included in the study. For these patients, the baseline and follow-up scans were acquired on the same multidetector CT scanner and using the same acquisition protocol. The CT scans were reconstructed with HR and standard RAs. We determined the difference in the EI between CT1 and CT2 for the HR and standard RAs, and we compared the variance of these differences.ResultsThe mean of the variation of the total lung volume was 0.14 L (standard deviation [SD] = 0.13 L) for the standard RA and 0.16 L (SD = 0.15 L) for the HR RA. These differences were not significant. For the standard RA, the mean variation was 0.13% (SD = 0.44%) for EI -970 and 0.4% (SD = 0.88%) for EI -950; for the HR RA, the mean variation was 1.9% (SD = 2.2%) for EI -970 and 3.6% (SD = 3.7%) for EI -950. These differences were significant.ConclusionUsing an HR RA appears to increase the variability of the CT measurements of the EI.

一种改进的凝视红外图像高分辨率重建算法

一种改进的凝视红外图像高分辨率重建算法

Correction for respiration artefacts in myocardial perfusion SPECT is more effective when reconstructions supporting collimator detector response compensation are applied

PurposeTo assess the impact of respiration on myocardial perfusion imaging (MPI) SPECT processed with advanced algorithmic reconstructions. MethodsSPECT studies obtained from a phantom simulation and 49 respiratory-gated, one-day 99mTc-sestamibi scans were corrected for respiratory-related cardiac movement. Three types of reconstruction algorithms: (a) filtered back projection (FBP), (b) ordered subset expectation maximization in which collimator detector response was incorporated (OSEM-CDR), and (c) OSEM-CDR with additional attenuation and scatter corrections (OSEM-CDR-ACSC) were applied to the corrected and uncorrected sets and analyzed quantitatively and qualitatively. ResultsA discrepancy between the corrected and uncorrected bull’s eye maps ≥10% was found in 2%, 10%, and 20% of the FBP, OSEM-CDR, and OSEM-CDR-ACSC scans, respectively. In studies with more than 10-mm respiratory motion, the effect of motion was greater in OSEM-CDR and OSEM-CDR-ACSC datasets as compared to FBP processing. Qualitative and quantitative differences between corrected and uncorrected sets were significantly larger in OSEM-CDR and OSEM-CDR-ACSC data than in those of FBP data. ConclusionsRespiratory-related cardiac motion significantly affects MPI-SPECT reconstructed with advanced high-resolution reconstruction algorithms such as OSEM-CDR and OSEM-CDR-ACSC and thus may justifies the application of respiratory gating.

Effect of reconstruction algorithm on image quality and identification of ground-glass opacities and partly solid nodules on low-dose thin-section CT: Experimental study using chest phantom

Purpose The purpose of this study was to assess the influence of reconstruction algorithm on identification and image quality of ground-glass opacities (GGOs) and partly solid nodules on low-dose thin-section CT. Materials and methods A chest CT phantom including simulated GGOs and partly solid nodules was scanned with five different tube currents and reconstructed by using standard (A) and newly developed (B) high-resolution reconstruction algorithms, followed by visually assessment of identification and image quality of GGOs and partly solid nodules by two chest radiologists. Inter-observer agreement, ROC analysis and ANOVA were performed to compare identification and image quality of each data set with those of the standard reference. The standard reference used 120 mA s in conjunction with reconstruction algorithm A. Results Kappa values ( κ) of overall identification and image qualities were substantial or almost perfect (0.60 < κ). Assessment of identification showed that area under the curve of 25 mA reconstructed with reconstruction algorithm A was significantly lower than that of standard reference ( p < 0.05), while assessment of image quality indicated that 50 mA s reconstructed with reconstruction algorithm A and 25 mA s reconstructed with both reconstruction algorithms were significantly lower than standard reference ( p < 0.05). Conclusion Reconstruction algorithm may be an important factor for identification and image quality of ground-glass opacities and partly solid nodules on low-dose CT examination.

A software tool for automatic image-based ventilation analysis using dynamic chest CT-scanning in healthy and in ARDS lungs

Density measurements in dynamic CT image series of the lungs allow one to quantify ventilated, hyperinflated, and atelectatic pulmonary compartments with high temporal resolution. Fast automatic segmentation of lung parenchyma and a subsequent evaluation of it's respective density values are a prerequisite for any clinical application of this technique. For automatic lung segmentation in thoracic CT scans, an algorithm was developed which uses (a) different density masks, and (b) anatomic knowledge to differentiate heart, diaphragm and chest wall from ventilated and atelectatic lung parenchyma. With Animal Care Committee approval, the automated technique was tested in 8 anaesthetized ventilated pigs undergoing dynamic CT before and after induction of lavage-ARDS. Images were acquired in one supradiaphragmatic, cross-sectional slice (temporal resolution of 100 ms; slice thickness of 1 mm, high resolution reconstruction algorithm). In 120 CT images the total pixel number and the calculated MLD from the automatically segmentated lung were compared to the values obtained from an interactive lung segmentation. The software tool was able to read all image series (DICOM standard). Automatic and interactive segmentation were in high agreement (R(2) = 0.99 for the total number of pixels and the MLD). Originally, the most frequent error was misclassification of atelectasis as extrapulmonary solid tissue. An automatic software tool is presented for lung segmentation in healthy lungs and in ARDS. Aerated lung and atelectasis were identified with high accuracy. This post-processing tool allows for a quantitative, CT based assessment of ventilation and recruitment processes in the lung. Thus, it may help to optimize ventilation patterns in patients with ARDS.

Basic principles of data acquisition and data processing for construction of high quality virtual models

Creating models for virtual reality subdivides into several steps. The aim of the data acquisition is the extraction of nearly isotropic (same solution in all three axes) data sets with low noise content. An approximate isotropy can be achieved by suitable choice of scan parameters. For raw data reconstruction, the application of high-resolution reconstruction algorithms is prohibited due to increased noise. A missing isotropy can computationally be approximated by interpolation. Further noise suppression is achieved by applying filters. Additionally, the contrast of the object for segmentation can be increased by image processing operators. The correct choice of the segmentation method and the editing tools is essential for a precise segmentation with minimal user interaction. Prior to visualization, smoothing the shape of the segmented model (shape-based or morphological interpolation, polygon reduction of wire frame model) further improves the visual appearance of the 3D model.

CT densitometry of the lungs: scanner performance.

Our goal was to establish the reproducibility and accuracy of the CT scanner in densitometry of the lungs. Scanner stability was assessed by analysis of daily quality checks. Studies using a humanoid phantom and polyethylene foams for lung were performed to measure reproducibility and accuracy. The dependence of the CT-estimated density on reconstruction filter, zoom factor, slice thickness, table height, data truncation, and objects outside the scan field was determined. Stability of the system at air density was within approximately 1 HU and at water density within approximately 2 HU. Reproducibility and accuracy for densities found for lung were within 2-3%. Dependence on the acquisition and reconstruction parameters was neglible, with the exceptions of the ultra high resolution reconstruction algorithm in the case of emphysema, and objects outside the scan field. The performance of the CT scanner tested is quite adequate for densitometry of the lungs.

COMPUTED TOMOGRAPHY (CT) OF THE MENISCI AND CRUCIATE LIGAMENTS

Preliminary experience using second generation CT scanners for non-invasive assessment of knee injuries was limited by technical and practical considerations The increased spatial and density resolution of the current generation CT scanners, and the capability of obtaining thin slices and computer reformation have prompted us to re-examine the application of CT for detecting meniscal and cruciate ligament injuries. The procedure is performed with the patient supine and the knees flexed 10° in the gantry. Approximately 20 contiguous 1.5 mm scans are obtained from the intercondylar notch to the tibial plateau. Subsequently, sagittal reformations and high resolution reconstruction algorithms (review) images are obtained. To date, 8 patients have been examined in this manner; 4 normal; 2 with abnormal medial menisci; and 2 with abnormal anterior cruciate ligaments. All had normal posterior cruciate ligaments. Review of these cases revealed gross visualization of the meniscus in most cases. Subtle tears of the menisci were not demonstrated. In one patient a surgically resected posterior horn of the medial meniscus was demonstrable by CT. Large tears of the menisci have not yet been examined. Sagittal reformations have enabled demonstration of both normal and abnormal cruciate ligaments. Six patients demonstrated normal anterior and posterior cruciate ligaments, findings confirmed by clinical and surgical observations. One patient demonstrated total rupture of the anterior cruciate and a second patient partial tear of the anterior cruciate, both surgically confirmed. Preliminary evaluation of advanced computed tomography for non-invasive detection of common injuries of the knees indicates that the cruciate ligaments can be easily evaluated by this method, that gross tears of the meniscus may be detectable, and that subtle meniscal tears are beyond current scanner resolution. Confirmation of these preliminary observations awaits experience with a larger patient population.