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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 interface...
We present a method for fast phase based registration of volume data for medical applications. As the number of different modalities within medical imaging increases, it becomes more and more important with registration that works for a mixture of modalities. For these applications the phase based registration approach has proven to be superior. Today there seem to be two kinds of groups that work...
We describe the implementation of an image reconstruction algorithm using the parallel processing capabilities of graphics processors. We are designing a new breast scanner which will allow simultaneous acquisition of PET and MRI images. The breast scanner is based on the technology of the much smaller RatCAP PET detector. The image reconstruction of the breast scanner poses a significant computing...
PROPELLER technique can effectively cancel motion artifacts in MRI. But its wider application in clinical situation is limited due to considerable reconstruction times. Since most correction operations in PROPELLER reconstruction can be done for each strip respectively, the algorithm is highly parallelizable. This allows us to exploit the data-parallel nature of the GPU fragment processors. The paper...
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