A survey of medical image registration on graphics hardware

Authors:
O. Fluck;C. Vetter;W. Wein;A. Kamen;B. Preim;R. Westermann
Affiliations:
Siemens Corporate Research, Princeton, NJ 08540, USA and Computer Science Department, Otto-von-Guericke-Universität, D-39106 Magdeburg, Germany;Siemens Corporate Research, Princeton, NJ 08540, USA and Computer Science Department, Technische Universität München, Garching 85748, Germany;Siemens Corporate Research, Princeton, NJ 08540, USA;Siemens Corporate Research, Princeton, NJ 08540, USA;Computer Science Department, Otto-von-Guericke-Universität, D-39106 Magdeburg, Germany;Computer Science Department, Technische Universität München, Garching 85748, Germany
Venue:
Computer Methods and Programs in Biomedicine
Year:
2011

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Abstract

The rapidly increasing performance of graphics processors, improving programming support and excellent performance-price ratio make graphics processing units (GPUs) a good option for a variety of computationally intensive tasks. Within this survey, we give an overview of GPU accelerated image registration. We address both, GPU experienced readers with an interest in accelerated image registration, as well as registration experts who are interested in using GPUs. We survey programming models and interfaces and analyze different approaches to programming on the GPU. We furthermore discuss the inherent advantages and challenges of current hardware architectures, which leads to a description of the details of the important building blocks for successful implementations.