Search results for "Back projection"

showing 3 items of 3 documents

Coronary CT angiography using iterative reconstruction 
vs. filtered back projection: evaluation of image quality.

2014

To compare image quality of iterative reconstruction algorithm(IRIS) vs. standard filtered back projection(FBP) reconstruction in CT Coronary Angiography (CTCA).Thirty-four consecutive patients underwent CTCA for suspected or known CAD with Dual-Source CT (DSCT-Flash, Siemens). All datasets were reconstructed with 0.75/0.4 and 0.6/0.4 mm slice thickness/increment, using three standard FBP kernels (B26-B30-B46) and three comparable IRIS algorithms (I26-I30-I46). Vascular attenuation and noise were measured. CT vascular attenuation values [HU] were measured in: ascending aorta (Ao), right (RCA) and left (LCA) coronary artery, respectively. Signal-to-noise (SNR) and contrast-to-noise (CNR) rat…

MaleImage Processing Computer-AssistedHumansFemaleCoronary Artery DiseaseProspective StudiesMiddle Agediterative reconstruction signal noise cardiac CT filtered back projectionSettore MED/36 - Diagnostica Per Immagini E RadioterapiaCoronary AngiographyTomography X-Ray ComputedAlgorithmsAged
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Implementation to Back-Projection Techniques of Resistivity Data

2005

In order to obtain well contrasted images by back-projection of resistivity data some modifications to the back-projection algorithm as well as the use of filtering techniques for the sensitivity matrix were proposed (Kotre 1994; Cosentino et al. 1998). To further improve the back-projection algorithm a new implementation is here suggested. Besides a subsequent filtering algorithm of the sensitivity coefficient matrix is proposed. It is aimed to increase resistivity contrasts and to reduce smoothness in tomographic final representation. Finally the proposed technique is tested on synthetic data.

OpticsElectrical resistivity and conductivitybusiness.industrySettore GEO/11 - Geofisica ApplicatabusinessBack-projection resistivity tomographyBack projectionGeologyNear Surface 2005 - 11th European Meeting of Environmental and Engineering Geophysics
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Approaching electrical tomography

2009

A general approach to electrical tomography is here described, based on the distribution of the experimental data to the set of voxels in which the subsoil has been divided. This approach utilizes the sensitivity coefficients as factors of the convolution procedure to execute the back projection of the data, to obtain the 3D pictures of the subsoil. A subsequent probabilistic filtering technique is described to improve the pictures in view of sharp boundary models. Some models are finally presented, mostly regarding cubic buried anomalies as well as pipe-shaped and L-shaped anomalies.

lcsh:QC801-809Probabilistic logicBoundary (topology)Geometrylcsh:QC851-999computer.software_genreConvolutionSet (abstract data type)Electrical tomographylcsh:Geophysics. Cosmic physicsGeophysicsDistribution (mathematics)Voxelelectrone gridback projectionlcsh:Meteorology. ClimatologySensitivity (control systems)TomographycomputerAlgorithmMathematicsAnnals of Geophysics
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