scholarly journals Dose Reduction and Low-Contrast Detectability Using Iterative CBCT Reconstruction Algorithm for Radiotherapy

2022 ◽  
Vol 21 ◽  
pp. 153303382110673
Author(s):  
Hayate Washio ◽  
Shingo Ohira ◽  
Yoshinori Funama ◽  
Yoshihiro Ueda ◽  
Masahiro Morimoto ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Similarity Index ◽  
Reconstruction Algorithm ◽  
Patient Dose ◽  
Reconstruction Technique ◽  
Registration Accuracy ◽  
Low Contrast ◽  
Full Dose ◽  
Reconstruction Methods ◽  
Imaging Dose

Introduction: Several studies have reported the relation between the imaging dose and secondary cancer risk and have emphasized the need to minimize the additional imaging dose as low as reasonably achievable. The iterative cone-beam computed tomography (iCBCT) algorithm can improve the image quality by utilizing scatter correction and statistical reconstruction. We investigate the use of a novel iCBCT reconstruction algorithm to reduce the patient dose while maintaining low-contrast detectability and registration accuracy. Methods: Catphan and anthropomorphic phantoms were analyzed. All CBCT images were acquired with varying dose levels and reconstructed with a Feldkamp–Davis–Kress algorithm-based CBCT (FDK-CBCT) and iCBCT. The low-contrast detectability was subjectively assessed using a 9-point scale by 4 reviewers and objectively assessed using structure similarity index (SSIM). The soft tissue-based registration error was analyzed for each dose level and reconstruction technique. Results: The results of subjective low-contrast detectability found that the iCBCT acquired at two-thirds of a dose was superior to the FDK-CBCT acquired at a full dose (6.4 vs 5.4). Relative to FDK-CBCT acquired at full dose, SSIM was higher for iCBCT acquired at one-sixth dose in head and head and neck region while equivalent with iCBCT acquired at two-thirds dose in pelvis region. The soft tissue-based registration was 2.2 and 0.6 mm for FDK-CBCT and iCBCT, respectively. Conclusion: Use of iCBCT reconstruction algorithm can generally reduce the patient dose by approximately two-thirds compared to conventional reconstruction methods while maintaining low-contrast detectability and accuracy of registration.

scholarly journals A CT Reconstruction Algorithm Based on L1/2Regularization

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Mianyi Chen ◽  
Deling Mi ◽  
Peng He ◽  
Luzhen Deng ◽  
Biao Wei
Keyword(s):  
Reconstruction Algorithm ◽  
Ct Images ◽  
Projection Data ◽  
Reconstruction Technique ◽  
Ct Reconstruction ◽  
Split Bregman ◽  
Reconstruction Methods ◽  
Significant Research ◽  
Regularization Operator

Computed tomography (CT) reconstruction with low radiation dose is a significant research point in current medical CT field. Compressed sensing has shown great potential reconstruct high-quality CT images from few-view or sparse-view data. In this paper, we use the sparser L1/2regularization operator to replace the traditional L1regularization and combine the Split Bregman method to reconstruct CT images, which has good unbiasedness and can accelerate iterative convergence. In the reconstruction experiments with simulation and real projection data, we analyze the quality of reconstructed images using different reconstruction methods in different projection angles and iteration numbers. Compared with algebraic reconstruction technique (ART) and total variance (TV) based approaches, the proposed reconstruction algorithm can not only get better images with higher quality from few-view data but also need less iteration numbers.

scholarly journals Registration accuracy with the low dose kilovoltage cone-beam CT: A phantom study

BJR|Open ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 20190028
Author(s):  
Yoshiki Takei ◽  
Hajime Monzen ◽  
Kenji Matsumoto ◽  
Kohei Hanaoka ◽  
Mikoto Tamura ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Image Quality ◽  
Image Registration ◽  
Low Dose ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
Registration Accuracy ◽  
Tube Current ◽  
Quality Aspect ◽  
Imaging Dose

Objective: The aim of this study was to investigate low-dose kilovoltage cone-beam CT (kV-CBCT) for image-guided radiotherapy, with a particular focus on the accuracy of image registration with low-dose protocols. Methods: Imaging doses were measured with a NOMEX semiconductor detector positioned at the front of head, thorax, and pelvis human body phantoms while kV-CBCT scans were acquired at different tube currents. Aspects of image quality (spatial resolution, noise, uniformity, contrast, geometric distortion, and Hounsfield unit sensitivity) and image registration accuracy using bone and soft tissue were evaluated. Results: With preset and the lowest tube currents, the imaging doses were 0.16 and 0.08 mGy, 5.29 and 2.80 mGy, and 18.23 and 2.69 mGy for head, thorax, and pelvis, respectively. Noise was the only quality aspect directly dependent on tube current, being increased by 1.5 times with a tube current half that of the preset in head and thorax, and by 2.2 times with a tube current 1/8 of the preset in the pelvis. Accurate auto-bone matching was performed within 1 mm at the lowest tube current. The auto-soft tissue matching could not be performed with the lowest tube current; however, manual-soft tissue matching could still be performed within 2 mm or less. Conclusion: Noise was the only image quality aspect dependent on the imaging dose. Auto-bone and manual-soft tissue matching could still be performed at the lowest imaging dose. Advances in knowledge: When optimizing kV-CBCT imaging dose, the impact on bone and soft tissue image registration accuracy should be evaluated.

PEMBELAJARAN SIMULASI PENCITRAAN CT DENGAN MENGGUNAKAN PRINSIP REKONSTRUKSI CITRA DALAM SOFTWARE MATLAB

2015 ◽  
Vol 8 (3) ◽  
pp. 161
Author(s):  
Samuel Gideon
Keyword(s):  
Image Reconstruction ◽  
Ct Imaging ◽  
The Body ◽  
Reconstruction Technique ◽  
Imaging Features ◽  
Back Projection ◽  
Cross Sectional ◽  
Low Contrast ◽  
Image Reconstruction Technique ◽  
Imaging Algorithms

This research was conducted as a learning alternatives for study of CT (computed tomograpghy) imaging using image reconstruction technique which are inversion matrix, back projection and filtered back projection. CT imaging can produce images of objects that do not overlap. Objects more easily distinguishable although given the relatively low contrast. The image is generated on CT imaging is the result of reconstruction of the original object. Matlab allows us to create and write imaging algorithms easily, easy to undersand and gives applied and exciting other imaging features. In this study, an example cross-sectional image recon-struction performed on the body of prostate tumors using. With these methods, medical prac-titioner (such as oncology clinician, radiographer and medical physicist) allows to simulate the reconstruction of CT images which almost resembles the actual CT visualization techniques.Keywords : computed tomography (CT), image reconstruction, Matlab

scholarly journals Evaluating a calcium-aware kernel for CT CAC scoring with varying surrounding materials and heart rates: a dynamic phantom study

2021 ◽  
Author(s):  
Niels R. van der Werf ◽  
Ronald Booij ◽  
Bernhard Schmidt ◽  
Thomas G. Flohr ◽  
Tim Leiner ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Soft Tissue ◽  
Patient Specific ◽  
Reconstruction Technique ◽  
Ct Reconstruction ◽  
Raw Data ◽  
Heart Rates ◽  
Tissue Equivalent ◽  
Tin Filtration ◽  
Reconstruction Kernel

Abstract Objectives The purpose of this study was twofold. First, the influence of a novel calcium-aware (Ca-aware) computed tomography (CT) reconstruction technique on coronary artery calcium (CAC) scores surrounded by a variety of tissues was assessed. Second, the performance of the Ca-aware reconstruction technique on moving CAC was evaluated with a dynamic phantom. Methods An artificial coronary artery, containing two CAC of equal size and different densities (196 ± 3, 380 ± 2 mg hydroxyapatite cm−3), was moved in the center compartment of an anthropomorphic thorax phantom at different heart rates. The center compartment was filled with mixtures, which resembled fat, water, and soft tissue equivalent CT numbers. Raw data was acquired with a routine clinical CAC protocol, at 120 peak kilovolt (kVp). Subsequently, reduced tube voltage (100 kVp) and tin-filtration (150Sn kVp) acquisitions were performed. Raw data was reconstructed with a standard and a novel Ca-aware reconstruction technique. Agatston scores of all reconstructions were compared with the reference (120 kVp) and standard reconstruction technique, with relevant deviations defined as > 10%. Results For all heart rates, Agatston scores for CAC submerged in fat were comparable to the reference, for the reduced-kVp acquisition with Ca-aware reconstruction kernel. For water and soft tissue, medium-density Agatston scores were again comparable to the reference for all heart rates. Low-density Agatston scores showed relevant deviations, up to 15% and 23% for water and soft tissue, respectively. Conclusion CT CAC scoring with varying surrounding materials and heart rates is feasible at patient-specific tube voltages with the novel Ca-aware reconstruction technique. Key Points • A dedicated calcium-aware reconstruction kernel results in similar Agatston scores for CAC surrounded by fatty materials regardless of CAC density and heart rate. • Application of a dedicated calcium-aware reconstruction kernel allows for radiation dose reduction. • Mass scores determined with CT underestimated physical mass.

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.

Multi-contrast CT imaging using a high energy resolution CdTe detector and a CZT photon-counting detector

2022 ◽  
Vol 17 (01) ◽  
pp. P01004
Author(s):  
N. Clements ◽  
D. Richtsmeier ◽  
A. Hart ◽  
M. Bazalova-Carter
Keyword(s):  
Contrast Agent ◽  
Energy Resolution ◽  
Photon Counting ◽  
High Energy ◽  
Ct Imaging ◽  
High Energy Resolution ◽  
Great Promise ◽  
Contrast Imaging ◽  
Low Contrast ◽  
Reconstruction Methods

Abstract Computed tomography (CT) imaging with high energy resolution detectors shows great promise in material decomposition and multi-contrast imaging. Multi-contrast imaging was studied by imaging a phantom with iodine (I), gadolinium (Gd), and gold (Au) solutions, and mixtures of the three using a cadmium telluride (CdTe) spectrometer with an energy resolution of 1% as well as with a cadmium zinc telluride (CZT) detector with an energy resolution of 13%. The phantom was imaged at 120 kVp and 1.1 mA with 7 mm of aluminum filtration. For the CdTe data collection, the phantom was imaged using a 0.2 mm diameter x-ray beam with 96 ten-second data acquisitions across the phantom at 45 rotation angles. For the CZT detector, we had 720 projections using a cone beam, and the six detector energy thresholds were set to 23, 33, 50, 64, 81, and 120 keV so that three thresholds corresponded to the K-edges of the contrast agents. Contrast agent isolation methods were then examined. K-edge subtraction and novel spectrometric algebraic image reconstruction (SAIR) were used for the CdTe data. K-edge subtraction alone was used for the CZT data. Linearity plots produced similar R 2 values and slopes for all three reconstruction methods. Comparing CdTe methods, SAIR offered less noise than CdTe K-edge subtraction and better geometric accuracy at low contrast concentrations. CdTe contrast agent images of I, Gd, and Au offered less noise and greater contrast than the CZT images, highlighting the benefits of high energy resolution CdTe detectors for possible use in pre-clinical or clinical CT imaging.

scholarly journals Application of Blind Deblurring Reconstruction Technique to SPECT Imaging

2007 ◽  
Vol 2007 ◽  
pp. 1-9 ◽  
Author(s):  
Heng Li ◽  
Yibin Zheng
Keyword(s):  
Experimental Studies ◽  
Small Animal ◽  
Ground Truth ◽  
Reconstruction Algorithm ◽  
Reconstruction Technique ◽  
Spect Image ◽  
Blind Deblurring ◽  
Image Blurring ◽  
Reconstruction Efficiency ◽  
Spect System

An SPECT image can be approximated as the convolution of the ground truth spatial radioactivity with the system point spread function (PSF). The PSF of an SPECT system is determined by the combined effect of several factors, including the gamma camera PSF, scattering, attenuation, and collimator response. It is hard to determine the SPECT system PSF analytically, although it may be measured experimentally. We formulated a blind deblurring reconstruction algorithm to estimate both the spatial radioactivity distribution and the system PSF from the set of blurred projection images. The algorithm imposes certain spatial-frequency domain constraints on the reconstruction volume and the PSF and does not otherwise assume knowledge of the PSF. The algorithm alternates between two iterative update sequences that correspond to the PSF and radioactivity estimations, respectively. In simulations and a small-animal study, the algorithm reduced image blurring and preserved the edges without introducing extra artifacts. The localized measurement shows that the reconstruction efficiency of SPECT images improved more than 50% compared to conventional expectation maximization (EM) reconstruction. In experimental studies, the contrast and quality of reconstruction was substantially improved with the blind deblurring reconstruction algorithm.

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