Characterization of a commercial hybrid iterative and model-based reconstruction algorithm in radiation oncology

2014 ◽  
Vol 41 (8Part1) ◽  
pp. 081907 ◽  
Author(s):  
Ryan G. Price ◽  
Sean Vance ◽  
Richard Cattaneo ◽  
Lonni Schultz ◽  
Mohamed A. Elshaikh ◽  
...  
Keyword(s):  
Radiation Oncology ◽  
Reconstruction Algorithm ◽  
Model Based

Model-based reconstruction algorithm in the detection of acute trauma-related lesions in brain CT examinations

2021 ◽  
pp. 197140092110087
Author(s):  
Andrea De Vito ◽  
Cesare Maino ◽  
Sophie Lombardi ◽  
Maria Ragusi ◽  
Cammillo Talei Franzesi ◽  
...  
Keyword(s):  
Image Quality ◽  
Iterative Reconstruction ◽  
Signal To Noise Ratio ◽  
Reconstruction Algorithm ◽  
Signal To Noise ◽  
Subjective Image Quality ◽  
Model Based ◽  
Hybrid Iterative Reconstruction ◽  
Noise Ratio ◽  
Enhanced Computed Tomography

Background and purpose To evaluate the added value of a model-based reconstruction algorithm in the assessment of acute traumatic brain lesions in emergency non-enhanced computed tomography, in comparison with a standard hybrid iterative reconstruction approach. Materials and methods We retrospectively evaluated a total of 350 patients who underwent a 256-row non-enhanced computed tomography scan at the emergency department for brain trauma. Images were reconstructed both with hybrid and model-based iterative algorithm. Two radiologists, blinded to clinical data, recorded the presence, nature, number, and location of acute findings. Subjective image quality was performed using a 4-point scale. Objective image quality was determined by computing the signal-to-noise ratio and contrast-to-noise ratio. The agreement between the two readers was evaluated using k-statistics. Results A subjective image quality analysis using model-based iterative reconstruction gave a higher detection rate of acute trauma-related lesions in comparison to hybrid iterative reconstruction (extradural haematomas 116 vs. 68, subdural haemorrhages 162 vs. 98, subarachnoid haemorrhages 118 vs. 78, parenchymal haemorrhages 94 vs. 64, contusive lesions 36 vs. 28, diffuse axonal injuries 75 vs. 31; all P<0.001). Inter-observer agreement was moderate to excellent in evaluating all injuries (extradural haematomas k=0.79, subdural haemorrhages k=0.82, subarachnoid haemorrhages k=0.91, parenchymal haemorrhages k=0.98, contusive lesions k=0.88, diffuse axonal injuries k=0.70). Quantitatively, the mean standard deviation of the thalamus on model-based iterative reconstruction images was lower in comparison to hybrid iterative one (2.12 ± 0.92 vsa 3.52 ± 1.10; P=0.030) while the contrast-to-noise ratio and signal-to-noise ratio were significantly higher (contrast-to-noise ratio 3.06 ± 0.55 vs. 1.55 ± 0.68, signal-to-noise ratio 14.51 ± 1.78 vs. 8.62 ± 1.88; P<0.0001). Median subjective image quality values for model-based iterative reconstruction were significantly higher ( P=0.003). Conclusion Model-based iterative reconstruction, offering a higher image quality at a thinner slice, allowed the identification of a higher number of acute traumatic lesions than hybrid iterative reconstruction, with a significant reduction of noise.

Analysis of Clinical Trials in Radiation Oncology: A Systematic Characterization of the Clinicaltrials.gov Database

2014 ◽  
Vol 90 (1) ◽  
pp. S581-S582 ◽  
Author(s):  
N. Cihoric ◽  
A. Tsikkinis ◽  
D.M. Aebersold ◽  
K. Lössl ◽  
K. Zaugg
Keyword(s):  
Clinical Trials ◽  
Radiation Oncology

scholarly journals Elasto-mammography: Theory, Algorithm, and Phantom Study

2006 ◽  
Vol 2006 ◽  
pp. 1-11 ◽  
Author(s):  
Z. G. Wang ◽  
Y. Liu ◽  
L. Z. Sun ◽  
G. Wang ◽  
L. L. Fajardo
Keyword(s):  
Elastic Moduli ◽  
Imaging Modality ◽  
Contrast Ratio ◽  
Reconstruction Algorithm ◽  
Displacement Measurement ◽  
Breast Compression ◽  
Before And After ◽  
Breast Tissues ◽  
Displacement Information

A new imaging modality framework, called elasto-mammography, is proposed to generate the elastograms of breast tissues based on conventional X-ray mammography. The displacement information is extracted from mammography projections before and after breast compression. Incorporating the displacement measurement, an elastography reconstruction algorithm is specifically developed to estimate the elastic moduli of heterogeneous breast tissues. Case studies with numerical breast phantoms are conducted to demonstrate the capability of the proposed elasto-mammography. Effects of noise with measurement, geometric mismatch, and elastic contrast ratio are evaluated in the numerical simulations. It is shown that the proposed methodology is stable and robust for characterization of the elastic moduli of breast tissues from the projective displacement measurement.

scholarly journals p-box: a new graph model

2015 ◽  
Vol Vol. 17 no. 1 (Graph Theory) ◽  
Author(s):  
Mauricio Soto ◽  
Christopher Thraves-Caro
Keyword(s):  
Graph Theory ◽  
Graph Model ◽  
Directed Path ◽  
Outerplanar Graphs ◽  
New Model ◽  
Model Based ◽  
Representative Element ◽  
International Audience ◽  
Graph Families

Graph Theory International audience In this document, we study the scope of the following graph model: each vertex is assigned to a box in ℝd and to a representative element that belongs to that box. Two vertices are connected by an edge if and only if its respective boxes contain the opposite representative element. We focus our study on the case where boxes (and therefore representative elements) associated to vertices are spread in ℝ. We give both, a combinatorial and an intersection characterization of the model. Based on these characterizations, we determine graph families that contain the model (e. g., boxicity 2 graphs) and others that the new model contains (e. g., rooted directed path). We also study the particular case where each representative element is the center of its respective box. In this particular case, we provide constructive representations for interval, block and outerplanar graphs. Finally, we show that the general and the particular model are not equivalent by constructing a graph family that separates the two cases.

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

Characterization of Energy Demand and Energy Services Using Model-Based and Data-Driven Approaches

2021 ◽  
pp. 229-248
Author(s):  
Carlos A. Santos Silva ◽  
Manar Amayri ◽  
Kaustav Basu
Keyword(s):  
Energy Demand ◽  
Data Driven ◽  
Energy Services ◽  
Model Based
Sign in / Sign up

Export Citation Format

Share Document