Iterative reconstruction algorithm which incorporates a high resolution anatomical image: simultaneous correction for 3-D detector response, attenuation, and scatter in SPECT neuroreceptor imaging

2002 ◽  
Author(s):  
H.-J. Kim ◽  
B.R. Zeeberg ◽  
R.C. Reba
Keyword(s):  
High Resolution ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
Detector Response ◽  
Iterative Reconstruction Algorithm ◽  
Anatomical Image ◽  
Neuroreceptor Imaging

scholarly journals GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Alan Pryor ◽  
Yongsoo Yang ◽  
Arjun Rana ◽  
Marcus Gallagher-Jones ◽  
Jihan Zhou ◽  
...  
Keyword(s):  
High Resolution ◽  
Iterative Reconstruction ◽  
3D Imaging ◽  
Reconstruction Algorithm ◽  
Iterative Reconstruction Algorithm

scholarly journals GENFIRE: A Generalized Fourier Iterative Reconstruction Algorithm for High-Resolution 3D Electron and X-ray Imaging

2017 ◽  
Vol 23 (S1) ◽  
pp. 128-129
Author(s):  
Alan Pryor ◽  
Yongsoo Yang ◽  
Arjun Rana ◽  
Marcus Gallagher-Jones ◽  
Jihan Zhou ◽  
...  
Keyword(s):  
High Resolution ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
X Ray ◽  
Iterative Reconstruction Algorithm ◽  
X Ray Imaging ◽  
3D Electron

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 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 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.

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