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Proceedings Paper

Implementing real-time adaptive filtering for medical applications on the cell processor using a generic multicore framework
Author(s): Olivier Bockenbach; Hauke Bartsch; Sebastian Schuberth
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Paper Abstract

Adaptive filtering is a compute-intensive algorithm aimed at effectively reducing noise without blurring the structures contained in a set of digital images. In this study, we take a generalized approach for adaptive filtering based on seven oriented filters, each individual filter implemented by a two-dimensional (2D) convolution with a mask size of 11 by 11 pixels. Digital radiology workflow imposes severe real-time constraints that require the use of hardware acceleration such as provided by multicore processors. Implementing complex algorithms on heterogeneous multicore architectures is a complex task especially for taking advantage of the DMA engines. We have implemented the algorithm on a Cell Broadband Engine (CBE) processor clocked at 3.2 GHz using a generic framework for multicore processors. This implementation is capable of filtering images of 5122 pixels at a throughput of 40 frames per second while allowing changing the parameters in real time. The resulting images are directed to the DR monitor or to the real-time computed tomography (CT) reconstruction engine.

Paper Details

Date Published: 1 March 2008
PDF: 9 pages
Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, 68120F (1 March 2008); doi: 10.1117/12.766306
Show Author Affiliations
Olivier Bockenbach, Mercury Computer Systems Inc. (United States)
Hauke Bartsch, Visage Imaging GmbH (Germany)
Sebastian Schuberth, Visage Imaging GmbH (Germany)

Published in SPIE Proceedings Vol. 6812:
Image Processing: Algorithms and Systems VI
Jaakko T. Astola; Karen O. Egiazarian; Edward R. Dougherty, Editor(s)

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