Recent applications of model-based iterative reconstruction(MBIR) algorithm to time-space Computed Tomography (CT) have shown that MBIR can greatly improve image quality by increasing resolution as well as reducing noise and some artifacts. Among the various iterative methods that have been studied for MBIR, iterative coordinate descent(ICD) has been found to have relatively low overall computational requirements due to its fast convergence. However, high computational cost and long reconstruction times remain as a barrier to the use of MBIR in practical applications. This disadvantage is especially prominent in time-space reconstruction because of the large volume of data. This thesis presents a new data structure, called VL-Buffer , for t...
maximization) algorithm and AWLS (one kind of multiplicative weighted least square) reconstruction, ...
There are many cases where one needs to limit the X-ray dose, or the number of projections, or both,...
In this work we have parallelized the Maximum Likelihood Expectation-Maximization (MLEM) and Ordered...
Recent applications of model-based iterative reconstruction(MBIR) algorithm to time-space Computed T...
Computed Tomography (CT) Image Reconstruction is an important technique used in a wide range of appl...
Recently it has been shown that model-based iterative reconstruction (MBIR) can greatly improve the ...
Computed Tomography (CT) Image Reconstruction is an important technique used in a wide range of appl...
AbstractBecause of its fast image acquisition and the rich diagnostic information it provides, compu...
Statistical iterative reconstruction is expected to improve the image quality of computed tomography...
Advanced MRI techniques often require sampling in additional (non-spatial) dimensions such as time o...
The iterative approach is important for computed tomography (CT) and attracting more and more attent...
The widespread emergence of parallel computers in the last decade has created a substantial programm...
This is the code and dataset for the paper: Accurate real space iterative reconstruction (RESIRE) al...
The framework of model-based iterative reconstruction (MBIR) is a versatile but powerful technique f...
In computed tomography, the application of iterative reconstruction methods in practical situations ...
maximization) algorithm and AWLS (one kind of multiplicative weighted least square) reconstruction, ...
There are many cases where one needs to limit the X-ray dose, or the number of projections, or both,...
In this work we have parallelized the Maximum Likelihood Expectation-Maximization (MLEM) and Ordered...
Recent applications of model-based iterative reconstruction(MBIR) algorithm to time-space Computed T...
Computed Tomography (CT) Image Reconstruction is an important technique used in a wide range of appl...
Recently it has been shown that model-based iterative reconstruction (MBIR) can greatly improve the ...
Computed Tomography (CT) Image Reconstruction is an important technique used in a wide range of appl...
AbstractBecause of its fast image acquisition and the rich diagnostic information it provides, compu...
Statistical iterative reconstruction is expected to improve the image quality of computed tomography...
Advanced MRI techniques often require sampling in additional (non-spatial) dimensions such as time o...
The iterative approach is important for computed tomography (CT) and attracting more and more attent...
The widespread emergence of parallel computers in the last decade has created a substantial programm...
This is the code and dataset for the paper: Accurate real space iterative reconstruction (RESIRE) al...
The framework of model-based iterative reconstruction (MBIR) is a versatile but powerful technique f...
In computed tomography, the application of iterative reconstruction methods in practical situations ...
maximization) algorithm and AWLS (one kind of multiplicative weighted least square) reconstruction, ...
There are many cases where one needs to limit the X-ray dose, or the number of projections, or both,...
In this work we have parallelized the Maximum Likelihood Expectation-Maximization (MLEM) and Ordered...