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Your search keyword '"Sorensen, Thomas Sangild"' showing total 11 results
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11 results on '"Sorensen, Thomas Sangild"'

3. Solid Mesh Registration for Radiotherapy Treatment Planning

Author

Noe, Karsten Østergaard, Sørensen, Thomas Sangild, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bello, Fernando, editor, and Cotin, Stéphane, editor

Published
2010
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4. An Introduction to GPU Accelerated Surgical Simulation

Author

Sørensen, Thomas Sangild, Mosegaard, Jesper, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Harders, Matthias, editor, and Székely, Gábor, editor

Published
2006
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6. Accelerating the nonequispaced fast fourier transform on commodity graphics hardware

Author

Sorensen, Thomas Sangild, Schaeffter, Tobias, Noe, Karsten Ostergaard, and Hansen, Michael Schacht

Subjects
Fourier transformations -- Evaluation, Magnetic resonance imaging -- Technology application, Graphics boards/cards -- Design and construction, Algorithms -- Usage, Graphics accelerator/display board, Sound/graphics board, Algorithm, Technology application, Business, Electronics, Electronics and electrical industries, Health care industry
Abstract

We present a fast parallel algorithm to compute the nonequispaced fast Fourier transform on commodity graphics hardware (the GPU). We focus particularly on a novel implementation of the convolution step in the transform as it was previously its most time consuming part. We describe the performance for two common sample distributions in medical imaging (radial and spiral trajectories), and for different convolution kernels as these parameters all influence the speed of the algorithm. The GPU-accelerated convolution is up to 85 times faster as our reference, the open source NFFT library on a state-of-the-art 64 bit CPU. The accuracy of the proposed GPU implementation was quantitatively evaluated at the various settings. To illustrate the applicability of the transform in medical imaging, in which it is also known as gridding, we look specifically at non-Cartesian magnetic resonance imaging and reconstruct both a numerical phantom and an in vivo cardiac image. Index Terms--Discrete Fourier transforms, magnetic resonance imaging (MRI), parallel algorithms, parallel architectures.

Published
2008

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