<p>We present one version of RS and ORS where there is no intermediate reconstruction step in test time (left) and on the a second version where intermediate reconstruction steps were incorporated, called RSv2 and ORSv2 (right). Figures show the median Root Mean Square Error (RMSE) performances of each method with respect to the median number of stimuli presentations. See Appendix A for details.</p
The high-resolution research tomograph (HRRT) is a dedicated human brain PET scanner. At present, it...
<p>The reconstruction algorithms performance is shown in terms of the relationship between precision...
<p>The four algorithms used are Nelder-Mead nonlinear simplex, Levenberg-Marquardt gradient descent,...
<p>The compare of reconstruction performance between SIRT, SART, MAP-EM and Iterative FBP (the image...
<p>SORS is compared to (left) existing and commercially used methods, (right) to SEP on mixed popula...
In many inverse problems with prior information, the measurement residual and the reconstruction err...
<p>We present the dependency of RMSE and number of presentations on MD on the left and right figures...
The presentation provides a comparison of SAR Tomographic Reconstruction Algorithm
Piecewise continuous reconstruction of real-valued data can be formulated in terms of non-convex opt...
A driving force for the development of new reconstruction algorithms is to achieve better quality im...
<p>Quality comparison of reconstructions based on matrices generated with Joseph’s and Siddon’s meth...
Columns from left to right show the reconstructed image, Log(RMSE), PSNR and UQI after two thousand ...
The performance of a super-resolution (SR) reconstruction method on real-world data is not easy to m...
peer reviewedThis study aimed at comparing the performance of filtered backprojection (FBP) and orde...
Abstract: Stochastic regularized methods are quite advantageous in Super-Resolution (SR) image recon...
The high-resolution research tomograph (HRRT) is a dedicated human brain PET scanner. At present, it...
<p>The reconstruction algorithms performance is shown in terms of the relationship between precision...
<p>The four algorithms used are Nelder-Mead nonlinear simplex, Levenberg-Marquardt gradient descent,...
<p>The compare of reconstruction performance between SIRT, SART, MAP-EM and Iterative FBP (the image...
<p>SORS is compared to (left) existing and commercially used methods, (right) to SEP on mixed popula...
In many inverse problems with prior information, the measurement residual and the reconstruction err...
<p>We present the dependency of RMSE and number of presentations on MD on the left and right figures...
The presentation provides a comparison of SAR Tomographic Reconstruction Algorithm
Piecewise continuous reconstruction of real-valued data can be formulated in terms of non-convex opt...
A driving force for the development of new reconstruction algorithms is to achieve better quality im...
<p>Quality comparison of reconstructions based on matrices generated with Joseph’s and Siddon’s meth...
Columns from left to right show the reconstructed image, Log(RMSE), PSNR and UQI after two thousand ...
The performance of a super-resolution (SR) reconstruction method on real-world data is not easy to m...
peer reviewedThis study aimed at comparing the performance of filtered backprojection (FBP) and orde...
Abstract: Stochastic regularized methods are quite advantageous in Super-Resolution (SR) image recon...
The high-resolution research tomograph (HRRT) is a dedicated human brain PET scanner. At present, it...
<p>The reconstruction algorithms performance is shown in terms of the relationship between precision...
<p>The four algorithms used are Nelder-Mead nonlinear simplex, Levenberg-Marquardt gradient descent,...