scholarly journals Azimuth Multichannel Reconstruction Based on Advanced Hyperbolic Range Equation

2021 ◽  
Vol 13 (22) ◽  
pp. 4705
Author(s):  
Wei Xu ◽  
Ruibo Li ◽  
Chonghua Fang ◽  
Pingping Huang ◽  
Weixian Tan ◽  
...  
Keyword(s):  
High Resolution ◽  
Phase Error ◽  
Reconstruction Algorithm ◽  
Doppler Spectrum ◽  
Time Varying ◽  
Reconstruction Algorithms ◽  
Additional Time ◽  
Frequency Dependent ◽  
Phase Errors ◽  
Range Equation

To acquire high-resolution wide-swath (HRWS) imaging capacity, the displaced phase center multichannel azimuth beam (DPCMAB) technology is usually adopted in spaceborne synthetic aperture radar (SAR), while multichannel reconstruction must be carried out before imaging process due to azimuth nonuniform sampling. Up to now, almost all azimuth multichannel reconstruction algorithms have been mainly based on conventional hyperbolic range equation (CHRE), but the accuracy of the CHRE model is usually not suitable for the HRWS mode, especially for high resolution and large squint observation cases. In this study, the azimuth multichannel signal model based on the advanced hyperbolic range equation (AHRE) is established and analyzed. The major difference between multichannel signal models based on CHRE and AHRE is the additional time-varying phase error between azimuth channels. The time-varying phase error is small and can be ignored in the monostatic DPCMAB SAR system, but it must be considered and compensated in the distributed DPCMAB SAR system. In addition to the time-varying phase error, additional Doppler spectrum shift and extended Doppler bandwidth should be considered in the squint case during azimuth multichannel reconstruction. The azimuth multichannel reconstruction algorithm based on AHRE is proposed in this paper. Before multichannel reconstruction and combination, time-varying phase errors between azimuth channels were first compensated, and the range-frequency-dependent de-skewing function was derived to remove the two-dimension (2D) spectrum tilt to avoid azimuth under-sampling. Then, azimuth multichannel data were reconstructed according to the azimuth multichannel impulse response based on AHRE. Finally, the range-frequency dependent re-skewing function was introduced to recover the tilted 2D spectrum. Simulation results on both point and distributed targets validated the proposed azimuth multichannel reconstruction approach.

scholarly journals Modified Chirp Scaling Algorithm for Ultra-High Resolution Spaceborne-SAR

2021 ◽  
Vol 2083 (3) ◽  
pp. 032048
Author(s):  
Tao He ◽  
Pengbo Wang ◽  
Jixiang Ma ◽  
Xinkai Zhou ◽  
Lingling Xue
Keyword(s):  
High Resolution ◽  
Phase Error ◽  
Equation Model ◽  
Synthetic Aperture ◽  
Signal Spectrum ◽  
Integration Time ◽  
Range Cell ◽  
Range Cell Migration ◽  
Range Equation ◽  
Chirp Scaling Algorithm

Abstract The hyperbolic range equation model (HREM) and equivalent squint range model (ESRM) are applied in traditional chirp scaling algorithm (CSA). However, these range models cannot describe the satellite range history in the high-resolution case accurately because of the long azimuth integration time. The non-negligible phase error caused by this will lead the targets distort. In this paper, a modified chirp scaling algorithm (MCSA) is proposed by introducing a novel high-precision range model. A more accurate signal spectrum is calculated through it. Then, the modified chirp scaling factor, range compression filter, range cell migration correction (RCMC) filter and azimuth compression filter can be derived based on this signal spectrum, and the focused target obtained at last. Finally, the experimental results, to validate the proposed algorithm, adopted by the sliding spotlight synthetic aperture radar (SAR) simulation are provided.

scholarly journals Focusing High-Resolution Airborne SAR with Topography Variations Using an Extended BPA Based on a Time/Frequency Rotation Principle

2018 ◽  
Vol 10 (8) ◽  
pp. 1275 ◽  
Author(s):  
Chunhui Lin ◽  
Shiyang Tang ◽  
Linrang Zhang ◽  
Ping Guo
Keyword(s):  
High Resolution ◽  
Time Domain ◽  
Phase Error ◽  
Projection Algorithm ◽  
Geometric Distortion ◽  
Back Projection ◽  
Time Frequency ◽  
Phase Errors ◽  
Airborne Sar ◽  
The Time Domain

With the increasing requirement for resolution, the negligence of topography variations causes serious phase errors, which leads to the degradation of the focusing quality of the synthetic aperture (SAR) imagery, and geometric distortion. Hence, a precise and fast algorithm is necessary for high-resolution airborne SAR. In this paper, an extended back-projection (EBP) algorithm is proposed to compensate the phase errors caused by topography variations. Three-dimensional (3D) variation will be processed in the time-domain for high-resolution airborne SAR. Firstly, the quadratic phase error (QPE) brought by topography variations is analyzed in detail for high-resolution airborne SAR. Then, the key operation, a time-frequency rotation operation, is applied to decrease the samplings in the azimuth time-domain. Just like the time-frequency rotation of the conventional two-step approach, this key operation can compress data in an azimuth time-domain and it reduces the computational burden of the conventional back-projection algorithm, which is applied lastly in the time-domain processing. The results of the simulations validate that the proposed algorithm, including frequency-domain processing and time-domain processing can obtain good focusing performance. At the same time, it has strong practicability with a small amount of computation, compared with the conventional algorithm.

scholarly journals Motion prediction enables simulated MR-imaging of freely moving model organisms

2019 ◽  
Author(s):  
Markus Reischl ◽  
Mazin Jouda ◽  
Neil MacKinnon ◽  
Erwin Fuhrer ◽  
Natalia Bakhtina ◽  
...  
Keyword(s):  
High Resolution ◽  
Region Of Interest ◽  
Magnetic Resonance Tomography ◽  
Reconstruction Algorithm ◽  
Model Organisms ◽  
Body Parts ◽  
C Elegans ◽  
Phase Errors ◽  
Freely Moving ◽  
The Impact

AbstractMagnetic resonance tomography typically applies the Fourier transform tok-space signals repeatedly acquired from a frequency encoded spatial region of interest, therefore requiring a stationary object during scanning. Any movement of the object results in phase errors in the recorded signal, leading to deformed images, phantoms, and artifacts, since the encoded information does not originate from the intended region of the object. However, if the type and magnitude of movement is known instantaneously, the scanner or the reconstruction algorithm could be adjusted to compensate for the movement, directly allowing high quality imaging with non-stationary objects. This would be an enormous boon to studies that tie cell metabolomics to spontaneous organism behaviour, eliminating the stress otherwise necessitated by restraining measures such as anesthesia or clamping.In the present theoretical study, we use a phantom of the animal modelC. elegansto examine the feasibility to automatically predict its movement and position, and to evaluate the impact of movement prediction, within a sufficiently long time horizon, on image reconstruction. For this purpose, we use automated image processing to annotate body parts in freely movingC. elegans, and predict their path of movement. We further introduce an MRI simulation platform based on brightfield-videos of the moving worm, combined with a stack of high resolution transmission electron microscope (TEM) slice images as virtual high resolution phantoms. A phantom provides an indication of the spatial distribution of signal-generating nuclei on a particular imaging slice. We show that adjustment of the scanning to the predicted movements strongly reduces distortions in the resulting image, opening the door for implementation in a high-resolution NMR scanner.

High-Resolution Computed Tomography Examinations for Chronic Suppurative Lung Disease in Early Childhood: Radiation Exposure and Image Quality Evaluations with Iterative Reconstruction Algorithm Use

2016 ◽  
Vol 67 (3) ◽  
pp. 218-224 ◽  
Author(s):  
Magdalini Smarda ◽  
Efstathios Efstathopoulos ◽  
Argyro Mazioti ◽  
Sofia Kordolaimi ◽  
Agapi Ploussi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
Image Quality ◽  
Radiation Exposure ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
Filtered Backprojection ◽  
Reconstruction Algorithms ◽  
High Resolution Computed Tomography ◽  
Iterative Reconstruction Algorithm

Purpose High radiosensitivity of children undergoing repetitive computed tomography examinations necessitates the use of iterative reconstruction algorithms in order to achieve a significant radiation dose reduction. The goal of this study is to compare the iDose iterative reconstruction algorithm with filtered backprojection in terms of radiation exposure and image quality in 33 chest high-resolution computed tomography examinations performed in young children with chronic bronchitis. Methods Fourteen patients were scanned using the filtered backprojection protocol while 19 patients using the iDose protocol and reduced milliampere-seconds, both on a 64-detector row computed tomography scanner. The iDose group images were reconstructed with different iDose levels (2, 4, and 6). Radiation exposure quantities were estimated, while subjective and objective image qualities were evaluated. Unpaired t tests were used for data statistical analysis. Results The iDose application allowed significant effective dose reduction (about 80%). Subjective image quality evaluation showed satisfactory results even with iDose level 2, whereas it approached excellent image with iDose level 6. Subjective image noise was comparable between the 2 groups with the use of iDose level 4, while objective noise was comparable between filtered backprojection and iterative reconstruction level 6 images. Conclusions The iDose algorithm use in pediatric chest high-resolution computed tomography reduces radiation exposure without compromising image quality. Further evaluation with iterative reconstruction algorithms is needed in order to establish high-resolution computed tomography as the gold standard low-dose method for children suffering from chronic lung diseases.

scholarly journals Multi-Layer Overlapped Subaperture Algorithm for Extremely-High-Squint High-Resolution Wide-Swath SAR Imaging with Continuously Time-Varying Radar Parameters

2022 ◽  
Vol 14 (2) ◽  
pp. 365
Author(s):  
Yan Wang ◽  
Rui Min ◽  
Zegang Ding ◽  
Tao Zeng ◽  
Linghao Li
Keyword(s):  
High Resolution ◽  
Second Phase ◽  
Time Varying ◽  
Constant Parameter ◽  
Signal Model ◽  
Phase Errors ◽  
Sar Imaging ◽  
Spatially Variant ◽  
Imaging Algorithms ◽  
Wide Swath

Extremely-high-squint (EHS) geometry of the traditional constant-parameter synthetic aperture radar (SAR) induces non-orthogonal wavenumber spectrum and hence the distortion of point spread function (PSF) in focused images. The method invented to overcome this problem is referred to as new-concept parameter-adjusting SAR. It corrects the PSF distortion by adjusting radar parameters, such as carrier frequency and chirp rate, based on instant data acquisition geometry. In this case, the characteristic of signal is quite different from the constant-parameter SAR and therefore, the traditional imaging algorithms cannot be directly applied for parameter-adjusting SAR imaging. However, the existing imaging algorithm for EHS parameter-adjusting SAR suffers from insufficient accuracy if a high-resolution wide-swath (HRWS) performance is required. Thus, this paper proposes a multi-layer overlapped subaperture algorithm (ML-OSA) for EHS HRWS parameter-adjusting SAR imaging with three main contributions: First, a more accurate signal model with time-varying radar parameters in high-squint geometry is derived. Second, phase errors are compensated with much higher accuracy by implementing multiple layers of coarse-to-fine spatially variant filters. Third, the analytical swath limit of the ML-OSA is derived by considering both the residual errors of signal model and phase compensations. The presented approach is validated via both the point- and extended-target computer simulations.

X-Ray Nanotomography (XRMT) Tool for Non-Destructive High-Resolution Imaging of ICs

2001 ◽  
Author(s):  
Wenbing Yun ◽  
Steve Wang ◽  
David Scott ◽  
Kenneth W. Nill ◽  
Waleed S. Haddad
Keyword(s):  
High Resolution ◽  
Process Development ◽  
3D Visualization ◽  
Tomographic Reconstruction ◽  
Reconstruction Algorithms ◽  
X Ray ◽  
Visualization Software ◽  
Volumetric Reconstruction ◽  
Resolution Imaging ◽  
Non Destructive

Abstract A high-resolution table-sized x-ray nanotomography (XRMT) tool has been constructed that shows the promise of nondestructively imaging the internal structure of a full IC stack with a spatial resolution better than 100 nm. Such a tool can be used to detect, localize, and characterize buried defects in the IC. By collecting a set of X-ray projections through the full IC (which may include tens of micrometers of silicon substrate and several layers of Cu interconnects) and applying tomographic reconstruction algorithms to these projections, a 3D volumetric reconstruction can be obtained, and analyzed for defects using 3D visualization software. XRMT is a powerful technique that will find use in failure analysis and IC process development, and may facilitate or supplant investigations using SEM, TEM, and FIB tools, which generally require destructive sample preparation and a vacuum environment.

scholarly journals Comparison between silicon photomultiplier-based and conventional PET/CT in patients with suspected lung cancer—a pilot study

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Johan Economou Lundeberg ◽  
Jenny Oddstig ◽  
Ulrika Bitzén ◽  
Elin Trägårdh
Keyword(s):  
Lung Cancer ◽  
Expectation Maximization ◽  
Image Interpretation ◽  
Imaging Study ◽  
Reconstruction Algorithm ◽  
Tnm Staging ◽  
Reconstruction Algorithms ◽  
Silicon Photomultiplier ◽  
Standardized Uptake Values ◽  
Pet Ct

Abstract Background Lung cancer is one of the most common cancers in the world. Early detection and correct staging are fundamental for treatment and prognosis. Positron emission tomography with computed tomography (PET/CT) is recommended clinically. Silicon (Si) photomultiplier (PM)-based PET technology and new reconstruction algorithms are hoped to increase the detection of small lesions and enable earlier detection of pathologies including metastatic spread. The aim of this study was to compare the diagnostic performance of a SiPM-based PET/CT (including a new block-sequential regularization expectation maximization (BSREM) reconstruction algorithm) with a conventional PM-based PET/CT including a conventional ordered subset expectation maximization (OSEM) reconstruction algorithm. The focus was patients admitted for 18F-fluorodeoxyglucose (FDG) PET/CT for initial diagnosis and staging of suspected lung cancer. Patients were scanned on both a SiPM-based PET/CT (Discovery MI; GE Healthcare, Milwaukee, MI, USA) and a PM-based PET/CT (Discovery 690; GE Healthcare, Milwaukee, MI, USA). Standardized uptake values (SUV) and image interpretation were compared between the two systems. Image interpretations were further compared with histopathology when available. Results Seventeen patients referred for suspected lung cancer were included in our single injection, dual imaging study. No statically significant differences in SUVmax of suspected malignant primary tumours were found between the two PET/CT systems. SUVmax in suspected malignant intrathoracic lymph nodes was 10% higher on the SiPM-based system (p = 0.026). Good consistency (14/17 cases) between the PET/CT systems were found when comparing simplified TNM staging. The available histology results did not find any obvious differences between the systems. Conclusion In a clinical setting, the new SiPM-based PET/CT system with a new BSREM reconstruction algorithm provided a higher SUVmax for suspected lymph node metastases compared to the PM-based system. However, no improvement in lung cancer detection was seen.

scholarly journals Performance Analysis of Surface Reconstruction Algorithms in Vertical Scanning Interferometry Based on Coherence Envelope Detection

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 164
Author(s):  
Dongxu Wu ◽  
Fusheng Liang ◽  
Chengwei Kang ◽  
Fengzhou Fang
Keyword(s):  
Surface Reconstruction ◽  
Measurement Accuracy ◽  
Experimental Studies ◽  
Reconstruction Algorithm ◽  
Low Noise ◽  
Surface Measurement ◽  
Reconstruction Algorithms ◽  
Centroid Method ◽  
Envelope Detection ◽  
Vertical Scanning Interferometry

Optical interferometry plays an important role in the topographical surface measurement and characterization in precision/ultra-precision manufacturing. An appropriate surface reconstruction algorithm is essential in obtaining accurate topography information from the digitized interferograms. However, the performance of a surface reconstruction algorithm in interferometric measurements is influenced by environmental disturbances and system noise. This paper presents a comparative analysis of three algorithms commonly used for coherence envelope detection in vertical scanning interferometry, including the centroid method, fast Fourier transform (FFT), and Hilbert transform (HT). Numerical analysis and experimental studies were carried out to evaluate the performance of different envelope detection algorithms in terms of measurement accuracy, speed, and noise resistance. Step height standards were measured using a developed interferometer and the step profiles were reconstructed by different algorithms. The results show that the centroid method has a higher measurement speed than the FFT and HT methods, but it can only provide acceptable measurement accuracy at a low noise level. The FFT and HT methods outperform the centroid method in terms of noise immunity and measurement accuracy. Even if the FFT and HT methods provide similar measurement accuracy, the HT method has a superior measurement speed compared to the FFT method.

scholarly journals High-Resolution ISAR Imaging and Autofocusing via 2D-ADMM-Net

2021 ◽  
Vol 13 (12) ◽  
pp. 2326
Author(s):  
Xiaoyong Li ◽  
Xueru Bai ◽  
Feng Zhou
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Phase Error ◽  
Random Phase ◽  
Back Propagation ◽  
Estimation Method ◽  
Data Driven ◽  
Reconstruction Performance ◽  
Imaging Results ◽  
Isar Imaging

A deep-learning architecture, dubbed as the 2D-ADMM-Net (2D-ADN), is proposed in this article. It provides effective high-resolution 2D inverse synthetic aperture radar (ISAR) imaging under scenarios of low SNRs and incomplete data, by combining model-based sparse reconstruction and data-driven deep learning. Firstly, mapping from ISAR images to their corresponding echoes in the wavenumber domain is derived. Then, a 2D alternating direction method of multipliers (ADMM) is unrolled and generalized to a deep network, where all adjustable parameters in the reconstruction layers, nonlinear transform layers, and multiplier update layers are learned by an end-to-end training through back-propagation. Since the optimal parameters of each layer are learned separately, 2D-ADN exhibits more representation flexibility and preferable reconstruction performance than model-driven methods. Simultaneously, it is able to better facilitate ISAR imaging with limited training samples than data-driven methods owing to its simple structure and small number of adjustable parameters. Additionally, benefiting from the good performance of 2D-ADN, a random phase error estimation method is proposed, through which well-focused imaging can be acquired. It is demonstrated by experiments that although trained by only a few simulated images, the 2D-ADN shows good adaptability to measured data and favorable imaging results with a clear background can be obtained in a short time.

scholarly journals Manual kidney stone size measurements in computed tomography are most accurate using multiplanar image reformatations and bone window settings

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Robert Peter Reimer ◽  
Konstantin Klein ◽  
Miriam Rinneburger ◽  
David Zopfs ◽  
Simon Lennartz ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Treatment Decision ◽  
Reconstruction Algorithm ◽  
Slice Thickness ◽  
Reconstruction Algorithms ◽  
Stone Size ◽  
Bone Window ◽  
3D Printed ◽  
Measurement Strategies ◽  
Digital Caliper

AbstractComputed tomography in suspected urolithiasis provides information about the presence, location and size of stones. Particularly stone size is a key parameter in treatment decision; however, data on impact of reformatation and measurement strategies is sparse. This study aimed to investigate the influence of different image reformatations, slice thicknesses and window settings on stone size measurements. Reference stone sizes of 47 kidney stones representative for clinically encountered compositions were measured manually using a digital caliper (Man-M). Afterwards stones were placed in a 3D-printed, semi-anthropomorphic phantom, and scanned using a low dose protocol (CTDIvol 2 mGy). Images were reconstructed using hybrid-iterative and model-based iterative reconstruction algorithms (HIR, MBIR) with different slice thicknesses. Two independent readers measured largest stone diameter on axial (2 mm and 5 mm) and multiplanar reformatations (based upon 0.67 mm reconstructions) using different window settings (soft-tissue and bone). Statistics were conducted using ANOVA ± correction for multiple comparisons. Overall stone size in CT was underestimated compared to Man-M (8.8 ± 2.9 vs. 7.7 ± 2.7 mm, p < 0.05), yet closely correlated (r = 0.70). Reconstruction algorithm and slice thickness did not significantly impact measurements (p > 0.05), while image reformatations and window settings did (p < 0.05). CT measurements using multiplanar reformatation with a bone window setting showed closest agreement with Man-M (8.7 ± 3.1 vs. 8.8 ± 2.9 mm, p < 0.05, r = 0.83). Manual CT-based stone size measurements are most accurate using multiplanar image reformatation with a bone window setting, while measurements on axial planes with different slice thicknesses underestimate true stone size. Therefore, this procedure is recommended when impacting treatment decision.

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