scholarly journals The results of approbation of a comprehensive expert assessment of the quality of CT images of the chest obtained on low-dose scanning protocols using iterative reconstruction methods

2021 ◽  
Vol 12 (3) ◽  
pp. 54-71
Author(s):  
G. V. Berkovich ◽  
A. V. Vodovatov ◽  
L. A. Chipiga ◽  
G. E. Trufanov
Keyword(s):  
Iterative Reconstruction ◽  
Low Dose ◽  
Ct Images ◽  
Expert Assessment ◽  
Reconstruction Algorithms ◽  
Suspected Infection ◽  
Reconstruction Methods ◽  
Method Of Assessment ◽  
Ct Image Quality

Introduction. Сomputed tomography (CT) is associated with high individual patient doses. Hence, the process of optimization in CT examinations by developing low-dose scan protocols is important.Purpose of the study. Clinical approbation of low-dose protocols developed by the authors earlier, selection of the most promising protocol, assessment of the applicability of the developed algorithm for expert assessment of the quality of CT images.Materials and methods. The study was based on the data from 96 patients who underwent cardiac surgery with suspected infection in the lungs or sternal wound infection. CT examinations were performed using standard, low-dose and ultra-low-dose protocols (effective dose 3,5±0,9, 1,7±0,1 and 0,8±0,1 mSv, respectively) using two iterative reconstruction algorithms (IMR and iDose). The quality of the obtained data was assessed by 5 radiologists with more than 5-year experience in chest radiology.Results. In terms of the number of misinterpretations, no significant differences were estimated between the standard and lowdose protocols for all reconstruction methods. The ultra-low-dose protocol was characterized by a significantly higher number of missing lesions compared to other protocols.Conclusion. The developed method of assessment of the CT image quality has proven to be informative and reproducible and can be used to assess new scanning protocols.

scholarly journals The influence of model iterative reconstruction on image quality in standard and low-dose computer tomography of the chest. experimental study.

2020 ◽  
Author(s):  
Антон Yu. Silin ◽  
Ivan S. Gruzdev ◽  
Sergey P. Morozov
Keyword(s):  
Radiation Dose ◽  
Dose Reduction ◽  
Spatial Resolution ◽  
Iterative Reconstruction ◽  
Low Dose ◽  
Reconstruction Algorithms ◽  
Anthropomorphic Phantom ◽  
Pulmonary Lesions ◽  
Calibration Phantom

Background: One of the ways to reduce the radiation dose in CT is to improve image reconstruction algorithms. The latest offer from scanner manufacturers is Model Iterative Reconstruction (MIR). Aims: To compare the quality of visualization of the structures of the organs of the chest and to prove the effectiveness of the low-dose protocol with iterative model reconstruction. Materials and methods: A calibration phantom with a spatial resolution module and an anthropomorphic phantom of the upper body of an adult with nodules in the lungs was scanned on two CT scanners of different manufacturers using the standard dose protocol (SDCT) with algorithms of hybrid iterative reconstruction (HIR) of images and MIR and low-dose protocol (LDCT) and MIR algorithm. The quality of the obtained images was evaluated by the parameters: noise (SD), the contrast-to-noise ratio (CNR), spatial resolution and visualization of pulmonary nodules. The radiation dose was calculated according to the scanner data, the data of individual dosimeters placed on the anthropomorphic phantom, and using a dosimetric phantom. Results: The average SD was 11.5; 24.4 and 21.6; CNR 85.47; 40.6 and 45.6; spatial resolution 2 mm; 2 mm and 3 mm for SDCT with MIR, SDCT with HIR and LDCT with MIR, respectively. Visualization of pulmonary lesions remained excellent in all cases. The radiation dose in case of SDCT was 2.7, and in case of LDCT - 0.67 mSv. The dose reduction was confirmed by dosimeter data. Similar results were obtained by repeating the experiment on a second scanner. Conclusions: The average SD was 11.5; 24.4 and 21.6; CNR 85.47; 40.6 and 45.6; spatial resolution 2 mm; 2 mm and 3 mm for SDCT with MIR, SDCT with HIR and LDCT with MIR, respectively. Visualization of pulmonary lesions remained excellent in all cases. The radiation dose in case of SDCT was 2.7, and in case of LDCT - 0.67 mSv. The dose reduction was confirmed by dosimeter data. Similar results were obtained by repeating the experiment on a second scanner.

scholarly journals Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Hsuan-Ming Huang ◽  
Ing-Tsung Hsiao
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Low Dose ◽  
Computational Cost ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Acceleration Techniques ◽  
Reconstruction Methods ◽  
Speed Up ◽  
Phantom Studies

Background and Objective. Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques.Methods. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively.Results. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method.Conclusions. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

scholarly journals Evaluation of Algebraic Iterative Image Reconstruction Methods for Tetrahedron Beam Computed Tomography Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-14
Author(s):  
Joshua Kim ◽  
Huaiqun Guan ◽  
David Gersten ◽  
Tiezhi Zhang
Keyword(s):  
Computed Tomography ◽  
Iterative Reconstruction ◽  
Cone Angle ◽  
Iterative Algorithms ◽  
Projection Data ◽  
Reconstruction Algorithms ◽  
Reconstruction Methods ◽  
Large Cone Angle ◽  
Using Data ◽  
Dual Detector

Tetrahedron beam computed tomography (TBCT) performs volumetric imaging using a stack of fan beams generated by a multiple pixel X-ray source. While the TBCT system was designed to overcome the scatter and detector issues faced by cone beam computed tomography (CBCT), it still suffers the same large cone angle artifacts as CBCT due to the use of approximate reconstruction algorithms. It has been shown that iterative reconstruction algorithms are better able to model irregular system geometries and that algebraic iterative algorithms in particular have been able to reduce cone artifacts appearing at large cone angles. In this paper, the SART algorithm is modified for the use with the different TBCT geometries and is tested using both simulated projection data and data acquired using the TBCT benchtop system. The modified SART reconstruction algorithms were able to mitigate the effects of using data generated at large cone angles and were also able to reconstruct CT images without the introduction of artifacts due to either the longitudinal or transverse truncation in the data sets. Algebraic iterative reconstruction can be especially useful for dual-source dual-detector TBCT, wherein the cone angle is the largest in the center of the field of view.

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