scholarly journals An iterative reconstruction algorithm for Faraday tomography

2020 ◽  
Vol 500 (4) ◽  
pp. 5129-5141
Author(s):  
Suchetha Cooray ◽  
Tsutomu T Takeuchi ◽  
Takuya Akahori ◽  
Yoshimitsu Miyashita ◽  
Shinsuke Ideguchi ◽  
...  
Keyword(s):  
Broad Band ◽  
Reconstruction Algorithm ◽  
Dispersion Function ◽  
Polarization Angle ◽  
Polarization Spectrum ◽  
Iterative Reconstruction Algorithm ◽  
Iterative Model ◽  
Reconstruction Performance ◽  
Frequency Coverage ◽  
Model Independent

ABSTRACT Faraday tomography offers crucial information on the magnetized astronomical objects, such as quasars, galaxies, or galaxy clusters, by observing its magnetoionic media. The observed linear polarization spectrum is inverse Fourier transformed to obtain the Faraday dispersion function (FDF), providing us a tomographic distribution of the magnetoionic media along the line of sight. However, this transform gives a poor reconstruction of the FDF because of the instrument’s limited wavelength coverage. The current Faraday tomography techniques’ inability to reliably solve the above inverse problem has noticeably plagued cosmic magnetism studies. We propose a new algorithm inspired by the well-studied area of signal restoration, called the Constraining and Restoring iterative Algorithm for Faraday Tomography (craft). This iterative model-independent algorithm is computationally inexpensive and only requires weak physically motivated assumptions to produce high fidelity FDF reconstructions. We demonstrate an application for a realistic synthetic model FDF of the Milky Way, where craft shows greater potential over other popular model-independent techniques. The dependence of observational frequency coverage on the various techniques’ reconstruction performance is also demonstrated for a simpler FDF. craft exhibits improvements even over model-dependent techniques (i.e. QU-fitting) by capturing complex multiscale features of the FDF amplitude and polarization angle variations within a source. The proposed approach will be of utmost importance for future cosmic magnetism studies, especially with broad-band polarization data from the Square Kilometre Array and its precursors. We make the craft code publicly available†.

scholarly journals Constrained Backtracking Matching Pursuit Algorithm for Image Reconstruction in Compressed Sensing

2021 ◽  
Vol 11 (4) ◽  
pp. 1435
Author(s):  
Xue Bi ◽  
Lu Leng ◽  
Cheonshik Kim ◽  
Xinwen Liu ◽  
Yajun Du ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Compressed Sensing ◽  
Matching Pursuit ◽  
Reconstruction Algorithm ◽  
Energy Criterion ◽  
Step Size ◽  
Relationship Analysis ◽  
Support Set ◽  
Reconstruction Performance ◽  
Sparsity Level

Image reconstruction based on sparse constraints is an important research topic in compressed sensing. Sparsity adaptive matching pursuit (SAMP) is a greedy pursuit reconstruction algorithm, which reconstructs signals without prior information of the sparsity level and potentially presents better reconstruction performance than other greedy pursuit algorithms. However, SAMP still suffers from being sensitive to the step size selection at high sub-sampling ratios. To solve this problem, this paper proposes a constrained backtracking matching pursuit (CBMP) algorithm for image reconstruction. The composite strategy, including two kinds of constraints, effectively controls the increment of the estimated sparsity level at different stages and accurately estimates the true support set of images. Based on the relationship analysis between the signal and measurement, an energy criterion is also proposed as a constraint. At the same time, the four-to-one rule is improved as an extra constraint. Comprehensive experimental results demonstrate that the proposed CBMP yields better performance and further stability than other greedy pursuit algorithms for image reconstruction.

scholarly journals Computerized Tomography Image Features under the Reconstruction Algorithm in the Evaluation of the Effect of Ropivacaine Combined with Dexamethasone and Dexmedetomidine on Assisted Thoracoscopic Lobectomy

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yan Cui ◽  
Yang Sun ◽  
Meng Xia ◽  
Dan Yao ◽  
Jun Lei
Keyword(s):  
Fourier Transform ◽  
Iterative Reconstruction ◽  
Analytical Method ◽  
Reconstruction Algorithm ◽  
Ct Images ◽  
Image Features ◽  
Anesthesia Induction ◽  
Iterative Reconstruction Algorithm ◽  
Thoracoscopic Lobectomy ◽  
The Fourier Transform

This research was aimed to study CT image features based on the backprojection filtering reconstruction algorithm and evaluate the effect of ropivacaine combined with dexamethasone and dexmedetomidine on assisted thoracoscopic lobectomy to provide reference for clinical diagnosis. A total of 110 patients undergoing laparoscopic resection were selected as the study subjects. Anesthesia induction and nerve block were performed with ropivacaine combined with dexamethasone and dexmedetomidine before surgery, and chest CT scan was performed. The backprojection image reconstruction algorithm was constructed and applied to patient CT images for reconstruction processing. The results showed that when the overlapping step size was 16 and the block size was 32 × 32, the running time of the algorithm was the shortest. The resolution and sharpness of reconstructed images were better than the Fourier transform analytical method and iterative reconstruction algorithm. The detection rates of lung nodules smaller than 6 mm and 6–30 mm (92.35% and 95.44%) were significantly higher than those of the Fourier transform analytical method and iterative reconstruction algorithm (90.98% and 87.53%; 88.32% and 90.87%) ( P < 0.05 ). After anesthesia induction and lobectomy with ropivacaine combined with dexamethasone and dexmedetomidine, the visual analogue scale (VAS) decreased with postoperative time. The VAS score decreased to a lower level (1.76 ± 0.54) after five days. In summary, ropivacaine combined with dexamethasone and dexmedetomidine had better sedation and analgesia effects in patients with thoracoscopic lobectomy. CT images based on backprojection reconstruction algorithm had a high recognition accuracy for lung lesions.

scholarly journals Computed Tomography Image under Optimized Iterative Reconstruction Algorithm to Analyze the Characteristics of Blood Flow Field in Cerebral Aneurysm before and after Stent Implantation

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Kunyang Bao ◽  
Chao Liu ◽  
Jin Li ◽  
Xiang Liu ◽  
Wenzhang Luo ◽  
...  
Keyword(s):  
Blood Flow ◽  
Flow Field ◽  
Cerebral Aneurysm ◽  
Iterative Reconstruction ◽  
Stent Implantation ◽  
Cerebral Aneurysms ◽  
Reconstruction Algorithm ◽  
Ct Images ◽  
Iterative Reconstruction Algorithm ◽  
The Difference

In order to analyze the change characteristics of blood flow field in cerebral aneurysms before and after stent implantation, this study first constructed an optimized iterative reconstruction algorithm to reconstruct CT images of patients with cerebral aneurysms and used it to solve the problem of image sharpness. In addition, backprojection image reconstruction algorithm and Fourier transform analytic method were introduced. According to the CT images of cerebral arteries of patients, the lesions were presented in a three-dimensional and visual way through the reconstructed three-dimensional images, thus achieving the effects of simulation and simulation. The results showed that the sensitivity, specificity, and accuracy of the optimized iterative reconstruction algorithm were 90.78%, 83.27%, and 94.82%, which were significantly higher than those of the backprojection image reconstruction algorithm and Fourier transform analysis method, and the difference was statistically significant ( P < 0.05 ). Before operation, the blood flow velocity in the neck of aneurysm was 7.35 × 10−2 m/s, the exit velocity was 1.51 × 10−1 m/s, and the maximum velocity appeared in the upstream part of the exit. After passing through the aneurysm, the blood flow velocity began to decrease gradually, forming a vortex at the top of the tumor. After stent implantation, the neck and outlet velocities of cerebral aneurysm were 9.352 × 10−2 m/s and 1.897 × 10−2 m/s, respectively. The velocity of blood flow decreased after entering the aneurysm, and there was no vortex at the top of the aneurysm. Among the outlet velocities of arterial blood vessels, the velocity before stent implantation was significantly lower than that after stent implantation, and the difference was statistically significant ( P < 0.05 ). Compared with prestent, the shear force distribution on the wall of cerebral aneurysm showed a significant decrease, and the difference was statistically significant ( P < 0.05 ). To sum up, pelvic floor ultrasound based on hybrid iterative reconstruction algorithm has high accuracy in diagnosing the changes of blood flow field in cerebral aneurysms. The application of CT images in the diagnosis of cerebral aneurysms can objectively provide imaging data for clinical practice and has high application value.

scholarly journals Yebes 40 m radio telescope and the broad band Nanocosmos receivers at 7 mm and 3 mm for line surveys

2021 ◽  
Vol 645 ◽  
pp. A37
Author(s):  
F. Tercero ◽  
J. A. López-Pérez ◽  
J. D. Gallego ◽  
F. Beltrán ◽  
O. García ◽  
...  
Keyword(s):  
Radio Telescope ◽  
Signal To Noise Ratio ◽  
Broad Band ◽  
High Sensitivity ◽  
Lower Sensitivity ◽  
Molecular Chemistry ◽  
Long Baseline ◽  
New Instrumentation ◽  
Frequency Coverage ◽  
Technical Specifications

Context. Yebes 40 m radio telescope is the main and largest observing instrument at Yebes Observatory and is devoted to very long baseline interferometry (VLBI) and single-dish observations since 2010. It has been covering frequency bands between 2 GHz and 90 GHz in discontinuous and narrow windows in most cases in order to match the current needs of the European VLBI Network (EVN) and the Global Millimeter VLBI Array (GMVA). Aims. The Nanocosmos project, a European Union-funded synergy grant, has enabled an increase in the instantaneous frequency coverage of the Yebes 40 m radio telescope, making it possible to observe many molecular transitions with single tunings in single-dish mode. This reduces the observing time and maximises the output from the telescope. Methods. We present technical specifications of the recently installed 31.5−50 GHz (Q band) and 72−90.5 GHz (W band) receivers along with the main characteristics of the telescope at these frequency ranges. We observed IRC+10216, CRL 2688, and CRL 618, which harbour a rich molecular chemistry, to demonstrate the capabilities of the new instrumentation for spectral observations in single-dish mode. Results. Our results show the high sensitivity of the telescope in the Q band. The spectrum of IRC+10126 offers an unprecedented signal-to-noise ratio for this source in this band. On the other hand, the spectrum normalised by the continuum flux towards CRL 618 in the W band demonstrates that the 40 m radio telescope produces comparable results to those from the IRAM 30 m radio telescope, although with a lower sensitivity. The new receivers fulfil one of the main goals of Nanocosmos and open up the possibility to study the spectrum of different astrophysical media with unprecedented sensitivity.

scholarly journals Comparison of methods for sensitivity correction in Talbot–Lau computed tomography

2021 ◽  
Author(s):  
Lina Felsner ◽  
Philipp Roser ◽  
Andreas Maier ◽  
Christian Riess
Keyword(s):  
Iterative Reconstruction ◽  
Phase Contrast ◽  
Reconstruction Algorithm ◽  
General Purpose ◽  
Contrast Imaging ◽  
X Ray ◽  
Iterative Reconstruction Algorithm ◽  
Inhomogeneous Phase ◽  
The Cost ◽  
Residual Errors

Abstract Purpose In Talbot–Lau X-ray phase contrast imaging, the measured phase value depends on the position of the object in the measurement setup. When imaging large objects, this may lead to inhomogeneous phase contributions within the object. These inhomogeneities introduce artifacts in tomographic reconstructions of the object. Methods In this work, we compare recently proposed approaches to correct such reconstruction artifacts. We compare an iterative reconstruction algorithm, a known operator network and a U-net. The methods are qualitatively and quantitatively compared on the Shepp–Logan phantom and on the anatomy of a human abdomen. We also perform a dedicated experiment on the noise behavior of the methods. Results All methods were able to reduce the specific artifacts in the reconstructions for the simulated and virtual real anatomy data. The results show method-specific residual errors that are indicative for the inherently different correction approaches. While all methods were able to correct the artifacts, we report a different noise behavior. Conclusion The iterative reconstruction performs very well, but at the cost of a high runtime. The known operator network shows consistently a very competitive performance. The U-net performs slightly worse, but has the benefit that it is a general-purpose network that does not require special application knowledge.

scholarly journals Multislice Spiral Computed Tomography under Hybrid Iterative Reconstruction Algorithm in Staging Diagnosis of Bladder Cancer and Ceramide Glycosylation

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jun Liu ◽  
Xiaolong Jiang
Keyword(s):  
Optical Density ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
Spiral Ct ◽  
Glucosylceramide Synthase ◽  
Multislice Spiral Ct ◽  
Iterative Reconstruction Algorithm ◽  
Hybrid Iterative Reconstruction ◽  
Group 2 ◽  
Group 1

This study was to discuss the application of multislice spiral computed tomography (CT) in the staging diagnosis of bladder cancer and the effect of ceramide glycosylation. The hybrid iterative reconstruction algorithm was applied. Immunohistochemistry and western blot were used to detect the normal bladder tissues (30 cases) of GCS in group 1 (100 cases) and group 2. The scanned images of all the research objects were obtained, the images with the iterative reconstruction algorithm were reconstructed, and statistical analysis on the CT value under the algorithm was conducted. The results showed that the image quality, blood vessel sharpness, average image score, signal-to-noise ratio, and radiation dose after the spiral CT and iterative reconstruction algorithm all increased, while the noise value decreased. The optical density value of glucosylceramide synthase in group 2 patients increased by 71%, and the optical density value of group 1 increased by 29%. The optical density expression of glucosylceramide synthase in group 1 patients was significantly higher than that in the control group, and there was a statistical difference between the two ( P < 0.05 ). Among the results of multislice spiral CT for tumor staging, the lesions larger than 5 cm and in the range of 1.1–2 cm in diameter were more sensitive. In 41 patients, there were multiple lesions. A total of 142 cancer lesions were found. The diameter of the tissue ranged from 0.5 to 6.8 cm, with an average diameter of 2.03 ± 0.35 cm. The optical density of glucosylceramide synthase in the group 1 was 5526, and the optical density in group 2 was 2576. The OD expression of GCS in group 1 was greatly higher in contrast to that in group 2, and there was a statistical difference between the two groups ( P < 0.05 ). The multislice spiral CT examination under this algorithm found that the diagnosis and staging accuracy of lesions with a diameter greater than 5 cm and tumor diameters in the range of 1.1 to 2 cm was higher. The image processed by the hybrid iterative reconstruction algorithm had good effect, high definition, and accuracy.

scholarly journals Influence of model based iterative reconstruction algorithm on image quality of multiplanar reformations in reduced dose chest CT

2016 ◽  
Vol 5 (8) ◽  
pp. 205846011666229 ◽  
Author(s):  
Heloise Barras ◽  
Vincent Dunet ◽  
Anne-Lise Hachulla ◽  
Jochen Grimm ◽  
Catherine Beigelman-Aubry
Keyword(s):  
Image Quality ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
Chest Ct ◽  
Iterative Reconstruction Algorithm ◽  
Reduced Dose ◽  
Model Based ◽  
Multiplanar Reformations
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