Share Email Print
cover

Proceedings Paper

GPU programming for biomedical imaging
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Scientific computing is rapidly advancing due to the introduction of powerful new computing hardware, such as graphics processing units (GPUs). Affordable thanks to mass production, GPU processors enable the transition to efficient parallel computing by bringing the performance of a supercomputer to a workstation. We elaborate on some of the capabilities and benefits that GPU technology offers to the field of biomedical imaging. As practical examples, we consider a GPU algorithm for the estimation of position of interaction from photomultiplier (PMT) tube data, as well as a GPU implementation of the MLEM algorithm for iterative image reconstruction.

Paper Details

Date Published: 27 August 2015
PDF: 15 pages
Proc. SPIE 9594, Medical Applications of Radiation Detectors V, 95940G (27 August 2015); doi: 10.1117/12.2195217
Show Author Affiliations
Luca Caucci, College of Optical Sciences, The Univ. of Arizona (United States)
Ctr. for Gamma Ray Imaging, The Univ. of Arizona (United States)
Lars R. Furenlid, College of Optical Sciences, The Univ. of Arizona (United States)
Ctr. for Gamma Ray Imaging, The Univ. of Arizona (United States)


Published in SPIE Proceedings Vol. 9594:
Medical Applications of Radiation Detectors V
H. Bradford Barber; Lars R. Furenlid; Hans N. Roehrig, Editor(s)

© SPIE. Terms of Use
Back to Top