TY  - CONF
T1  - A Parallel Deconvolution Algorithm in Perfusion Imaging
T2  - Healthcare Informatics, Imaging, and Systems Biology (HISB)
Y1  - 2011
A1  - Zhu, Fan.
A1  - Rodríguez, David
A1  - Carpenter, Trevor
A1  - Malcolm Atkinson
A1  - Wardlaw, Joanna
KW  - Deconvolution
KW  - GPGPU
KW  - Parallelization
KW  - Perfusion Imaging
AB  - In this paper, we will present the implementation of a deconvolution algorithm for brain perfusion quantification on GPGPU (General Purpose Graphics Processor Units) using the CUDA programming model. GPUs originated as graphics generation dedicated co-processors, but the modern GPUs have evolved to become a more general processor capable of executing scientific computations. It provides a highly parallel computing environment due to its huge number of computing cores and constitutes an affordable high performance computing method. The objective of brain perfusion quantification is to generate parametric maps of relevant haemodynamic quantities such as Cerebral Blood Flow (CBF), Cerebral Blood Volume (CBV) and Mean Transit Time (MTT) that can be used in diagnosis of conditions such as stroke or brain tumors. These calculations involve deconvolution operations that in the case of using local Arterial Input Functions (AIF) can be very expensive computationally. We present the serial and parallel implementations of such algorithm and the evaluation of the performance gains using GPUs.
JF  - Healthcare Informatics, Imaging, and Systems Biology (HISB)
CY  - San Jose, California
SN  - 978-1-4577-0325-6
UR  - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6061411&tag=1
ER  -