CUDA Papers

A collection of research papers and projects utilizing CUDA technology

Tag Archives: MRI

Accelerating Advanced MRI Reconstructions on GPUs Abstract Computational acceleration on graphics processing units(GPUs) can make advanced magnetic resonance imaging(MRI) reconstruction algorithms attractive in clinical settings,thereby improving the quality of MR images across abroad spectrum of applications. At present, MR imaging isoften limited by high noise levels, signi cant imaging artifacts,and/or long data acquisition (scan) times. Advancedimage reconstruction algorithms can mitigate these […]

Accelerating Iterative Field-Compensated MR Image Reconstruction on GPUs Abstract We propose a fast implementation for iterative MR image reconstruction using Graphics Processing Units (GPU). In MRI, iterative reconstruction with conjugate gradient algorithms allows for accurate modeling the physics of the imaging system. Specifically, methods have been reported to compensate for the magnetic field inhomogeneity induced by the susceptibility differences near the air/tissue […]

Sparse regularization in MRI iterative reconstruction using GPUs Abstract Regularization is a common technique used toimprove image quality in inverse problems such as MR imagereconstruction. In this work, we extend our previous GraphicsProcessing Unit (GPU) implementation of MR imagereconstruction with compensation for susceptibility-induced fieldinhomogeneity effects by incorporating an additional quadraticregularization term. Regularization techniques commonly imposethe prior information that MR images are relatively […]