scholarly journals An Iterative CT Reconstruction Algorithm for Fast Fluid Flow Imaging

2015 ◽  
Vol 24 (11) ◽  
pp. 4446-4458 ◽  
Author(s):  
Geert Van Eyndhoven ◽  
K. Joost Batenburg ◽  
Daniil Kazantsev ◽  
Vincent Van Nieuwenhove ◽  
Peter D. Lee ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Reconstruction Algorithm ◽  
Flow Imaging ◽  
Ct Reconstruction ◽  
Iterative Ct Reconstruction

scholarly journals Parallelism of iterative CT reconstruction based on local reconstruction algorithm

2008 ◽  
Vol 48 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Junjun Deng ◽  
Hengyong Yu ◽  
Jun Ni ◽  
Lihe Wang ◽  
Ge Wang
Keyword(s):  
Reconstruction Algorithm ◽  
Ct Reconstruction ◽  
Local Reconstruction ◽  
Iterative Ct Reconstruction

scholarly journals Iterative CT reconstruction in abdominal low-dose CT used for hybrid SPECT-CT applications: effect on image quality, image noise, detectability, and reader’s confidence

2019 ◽  
Vol 8 (6) ◽  
pp. 205846011985626
Author(s):  
Oliver S Grosser ◽  
Juri Ruf ◽  
Dennis Kupitz ◽  
Damian Czuczwara ◽  
David Loewenthal ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Image Quality ◽  
Iterative Reconstruction ◽  
Bone Structure ◽  
Reconstruction Algorithm ◽  
Image Noise ◽  
Ct Reconstruction ◽  
Quality Image ◽  
Iterative Ct Reconstruction ◽  
Ct Data

Background Iterative computed tomography (CT) image reconstruction shows high potential for the preservation of image quality in diagnostic CT while reducing patients’ exposure; it has become available for low-dose CT (LD-CT) in high-end hybrid imaging systems (e.g. single-photon emission computed tomography [SPECT]-CT). Purpose To examine the effect of an iterative CT reconstruction algorithm on image quality, image noise, detectability, and the reader’s confidence for LD-CT data by a subjective assessment. Material and Methods The LD-CT data were validated for 40 patients examined by an abdominal hybrid SPECT-CT (U = 120 kV, I = 40 mA, pitch = 1.375). LD-CT was reconstructed using either filtered back projection (FBP) or an iterative image reconstruction algorithm (Adaptive Statistical Iterative Reconstruction [ASIR]®) with different parameters (ASIR levels 50% and 100%). The data were validated by two independent blinded readers using a scoring system for image quality, image noise, detectability, and reader confidence, for a predefined set of 16 anatomic substructures. Results The image quality was significantly improved by iterative reconstruction of the LD-CT data compared with FBP ( P ≤ 0.0001). While detectability increased in only 2/16 structures ( P ≤ 0.03), the reader’s confidence increased significantly due to iterative reconstruction ( P ≤ 0.002). Meanwhile, at the ASIR level of 100%, the detectability in bone structure was highly reduced ( P = 0.003). Conclusion An ASIR level of 50% represents a good compromise in abdominal LD-CT image reconstruction. The specific ASIR level improved image quality (reduced image noise) and reader confidence, while preserving detectability of bone structure.

scholarly journals Validation of iterative CT reconstruction by inter and intra observer performance assessment of artificial lung foci

2020 ◽  
Vol 6 (3) ◽  
pp. 534-537
Author(s):  
Britta König ◽  
Nika Guberina ◽  
Hilmar Kühl ◽  
Waldemar Zylka
Keyword(s):  
Low Dose ◽  
Lung Cancer Screening ◽  
Artificial Lung ◽  
Observer Performance ◽  
Subjective Perception ◽  
Ct Reconstruction ◽  
Perfect Agreement ◽  
Observer Reliability ◽  
Iterative Ct Reconstruction ◽  
Extension Ring

AbstractWe investigate the suitability of statistical and model-based iterative reconstruction (IR) algorithm strengths and their influence on image quality and diagnostic performance in low-dose computer tomography (CT) protocols for lung-cancer screening procedures. We evaluate the inter- and intra-observer performance for the assessment of iterative CT reconstruction. Artificial lung foci shaped as spheres and spicules made from material with calibrated Hounsfield units were pressed within layered granules in lung lobes of an anthropomorphic phantom. Adaptively, a soft-tissue- and fat- extension ring were attached. The phantom with foci was scanned using standard high contrast, low-dose and ultra lowdose protocols. For reconstruction the IR algorithm ADMIRE at four different strength levels were used. Two ranking tests and Friedman statistics were performed. Fleiss k and modified Cohen’s kneywere used to quantify inter- and intra-observer performance. In conjunction with the standard lung kernel BL75 radiologists evaluated medium to high IR strength, with preference to S4, as suitable for lung foci detection. When varying reconstruction kernels the ranking became more random than with varying phantom diameter. The inter-observer reliability shows poor to slight agreement expressed by k<0 and k=0-0.20 . For the intra-observer reliability non- agreement with kney=0-0.20and moderate agreement with kney=0.60-0.79 for the first ranking test, and almost perfect agreement with kney>0.90 for the second ranking test was observed. In conclusion, our validation suggests radiological preference of medium to high iteration strengths, especially S4, for lung foci detection. An investigation of the correlation between diagnostic experience and the subjective perception of IR reconstructed CT images still needs to be investigated.

scholarly journals CT reconstruction algorithm based on truncated TV

2021 ◽  
Vol 1920 (1) ◽  
pp. 012036
Author(s):  
Hongyan Shi ◽  
Aidi Wu ◽  
Shidi Yang ◽  
Dongjiang Ji
Keyword(s):  
Reconstruction Algorithm ◽  
Ct Reconstruction

scholarly journals Iterative CT Reconstruction Using Shearlet-Based Regularization

2013 ◽  
Vol 60 (5) ◽  
pp. 3305-3317 ◽  
Author(s):  
Bert Vandeghinste ◽  
Bart Goossens ◽  
Roel Van Holen ◽  
Christian Vanhove ◽  
Aleksandra Pizurica ◽  
...  
Keyword(s):  
Ct Reconstruction ◽  
Iterative Ct Reconstruction

scholarly journals X-RAY CT Reconstruction by using Spatially Non Homogeneous ICD Optimization

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2043-2046
Keyword(s):  
Search Algorithm ◽  
Computational Cost ◽  
Selection Criterion ◽  
Closed Form Solution ◽  
Helical Ct ◽  
Reconstruction Algorithm ◽  
Form Solution ◽  
Ct Reconstruction ◽  
Practical Applications ◽  
Voxel Selection

Recent applications of conventional iterative coordinate descent (ICD) algorithms to multislice helical CT reconstructions have shown that conventional ICD can greatly improve image quality by increasing resolution as well as reducing noise and some artifacts. However, high computational cost and long reconstruction times remain as a barrier to the use of conventional algorithm in the practical applications. Among the various iterative methods that have been studied for conventional, ICD has been found to have relatively low overall computational requirements due to its fast convergence. This paper presents a fast model-based iterative reconstruction algorithm using spatially nonhomogeneous ICD (NH-ICD) optimization. The NH-ICD algorithm speeds up convergence by focusing computation where it is most needed. The NH-ICD algorithm has a mechanism that adaptively selects voxels for update. First, a voxel selection criterion VSC determines the voxels in greatest need of update. Then a voxel selection algorithm VSA selects the order of successive voxel updates based upon the need for repeated updates of some locations, while retaining characteristics for global convergence. In order to speed up each voxel update, we also propose a fast 3-D optimization algorithm that uses a quadratic substitute function to upper bound the local 3-D objective function, so that a closed form solution can be obtained rather than using a computationally expensive line search algorithm. The experimental results show that the proposed method accelerates the reconstructions by roughly a factor of three on average for typical 3-D multislice geometries.

Differentiation between Symptomatic Chiari I Malformation and Asymptomatic Tonsilar Ectopia by Using Cerebrospinal Fluid Flow Imaging: Initial Estimate of Imaging Accuracy

Radiology ◽  
2007 ◽  
Vol 245 (2) ◽  
pp. 532-540 ◽  
Author(s):  
Shawn K. Hofkes ◽  
Bermans J. Iskandar ◽  
Patrick A. Turski ◽  
Lindell R. Gentry ◽  
Jeremy B. McCue ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Fluid Flow ◽  
Chiari I Malformation ◽  
Flow Imaging ◽  
Initial Estimate ◽  
Cerebrospinal Fluid Flow ◽  
Chiari I
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