Ian C. Atkinson, Geng Liu, Nady Obeid, Keith R. Thulborn, Wen-mei Hwu
Quantitative sodium magnetic resonance imaging permits noninvasive measurement of the tissue sodium concentration (TSC) bioscale in the brain. Computing the TSC bioscale requires reconstructing and combining multiple datasets acquired with a non-Cartesian acquisition that highly oversamples the center of k-space. Even with an optimized implementation of the algorithm to compute TSC, the overall processing time […]
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Sebastian Schaetz, Martin Uecker
We present MGPU, a C++ programming library targeted at single-node multi-GPU systems. Such systems combine disproportionate floating point performance with high data locality and are thus well suited to implement real-time algorithms. We describe the library design, programming interface and implementation details in light of this specific problem domain. The core concepts of this work […]
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A.M. Adeshina, R. Hashim, N.E.A. Khalid, Siti Z.Z. Abidin
The rapid development in information technology has immensely contributed to the use of modern approaches for visualizing volumetric data. Consequently, medical volume visualization is increasingly attracting attention towards achieving an effective visualization algorithm for medical diagnosis and pre-treatment planning. Previously, research has been addressing implementation of algorithm that can visualize 2-D images into 3-D. Meanwhile, […]
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Anders Eklund, Mats Andersson, Hans Knutsson
Functional magnetic resonance imaging (fMRI) makes it possible to non-invasively measure brain activity with high spatial resolution. There are however a number of issues that have to be addressed. One is the large amount of spatio-temporal data that needs to be processed. In addition to the statistical analysis itself, several preprocessing steps, such as slice […]
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Manuel Freiberger, Florian Knoll, Kristian Bredies, Hermann Scharfetter, Rudolf Stollberger
Fast image reconstruction is a critical requirement for an imaging modality to be adopted in the field of clinical and pre-clinical sciences. While programs become faster due to more powerful hardware, at the same time data size increases and the need for advanced—and often computational more demanding—reconstruction algorithms arises. A cheap way to achieve a […]
Cagdas Bilen, Yao Wang, Ivan Selesnick
Magnetic Resonance Imaging (MRI) is one of the fields that the compressed sensing theory is well utilized to reduce the scan time significantly leading to faster imaging or higher resolution images. It has been shown that a small fraction of the overall measurements are sufficient to reconstruct images with the combination of compressed sensing and […]
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Mark Murphy
Magnetic Resonance Imaging (MRI) is a non-invasive and highly exible medical imaging modality that does not expose patients ionizing radiation. MR Image acquisitions can be designed by varying a large number of contrast-generation parameters, and many clinical diagnostic applications exist. However, imaging speed is a fundamental limitation to many potential applications. Traditionally, MRI data have […]
Adelino R. Ferreira da Silva
Graphic processing units (GPUs) are rapidly gaining maturity as powerful general parallel computing devices. A key feature in the development of modern GPUs has been the advancement of the programming model and programming tools. Compute Unified Device Architecture (CUDA) is a software platform for massively parallel high-performance computing on Nvidia many-core GPUs. In functional magnetic […]
Xiao-Long Wu, Yue Zhuo, Fan Lam, Maojing Fu, Justin P. Haldar, Wen-Mei Hwu, Zhi-Pei Liang, Bradley P. Sutton, Jiading Gai
In this paper, we present a fast iterative magnetic resonance imaging (MRI) reconstruction algorithm taking advantage of the prevailing GPGPU programming paradigm. In clinical environment, MRI reconstruction is usually performed via fast Fourier transform (FFT). However, imaging artifacts (i.e. signal loss) resulting from susceptibility-induced magnetic field inhomogeneities degrade the quality of reconstructed images. These artifacts […]
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T.H.J.M. Peeters, V. Prckovska, M. van Almsick, A. Vilanova, B.M. ter Haar Romeny
High angular resolution diffusion imaging (HARDI) is an emerging magnetic resonance imaging (MRI) technique that overcomes some decisive limitations of its predecessor diffusion tensor imaging (DTI). HARDI can resolve locally more than one direction in the diffusion pattern of water molecules and thereby opens up the opportunity to display and track crossing fibers. Showing the […]
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J. Chi, F. Liu, J. Jin, D.G. Mason, S. Crozier
The finite difference time domain (FDTD) method is a popular technique for computational electromagnetics (CEM). The large computational power often required, however, has been a limiting factor for its applications. In this paper, we will present a graphics processing unit (GPU)-based parallel FDTD solver and its successful application to the investigation of a novel B1 […]
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B.D. de Senneville, K.O. Noe, M. Ries, M. Pedersen, C.T.W. Moonen, T.S. Sorensen
Magnetic resonance Imaging (MRI) can be used for non invasive temperature mapping and is therefore a promising tool to monitor and control interventional therapies based on thermal ablation. The proton resonance frequency shift MRI technique gives an estimate of the temperature by comparing phase changes between dynamically acquired images. These temperature measurements are prone to […]
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