Design and implementation of the software architecture for a 3-D reconstruction system in medical imaging

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Design and implementation of the software architecture for a 3-D reconstruction system in medical imaging

Full text

Pdf (209 KB)

Source

International Conference on Software Engineering archive
Proceedings of the 30th international conference on Software engineering table of contents

Leipzig, Germany

SESSION: Architecture table of contents

Pages 661-668

Year of Publication: 2008

ISBN:978-1-60558-079-1

Authors

Holger Scherl	University of Erlangen-Nuremberg, Erlangen, Germany
Stefan Hoppe	University of Erlangen-Nuremberg, Erlangen, Germany
Markus Kowarschik	Siemens Medical Solutions, Erlangen, Germany
Joachim Hornegger	University of Erlangen-Nuremberg, Erlangen, Germany

Sponsors

ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 12, Downloads (12 Months): 167, Citation Count: 0

Additional Information:

abstract references index terms collaborative colleagues

Tools and Actions:	Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/1368088.1368181 What is a DOI?

ABSTRACT

The design and implementation of the reconstruction system in medical X-ray imaging is a challenging issue due to its immense computational demands. In order to ensure an efficient clinical workflow it is inevitable to meet high performance requirements. Hence, the usage of hardware acceleration is mandatory. The software architecture of the reconstruction system is required to be modular in a sense that different accelerator hardware platforms are supported and it must be possible to implement different parts of the algorithm using different acceleration architectures and techniques.

This paper introduces and discusses the design of a software architecture for an image reconstruction system that meets the aforementioned requirements. We implemented a multi-threaded software framework that combines two software design patterns: the pipeline and the master/worker pattern. This enables us to take advantage of the parallelism in off-the-shelf accelerator hardware such as multi-core systems, the Cell processor, and graphics accelerators in a very flexible and reusable way.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Andrei Alexandrescu, Modern C++ design: generic programming and design patterns applied, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 2001
	2	L. A. Feldkamp, L. C. Davis, and J. W. Kress. Practical cone-beam algorithm. J. Opt. Soc. Amer., A1(6):612--619, 1984.
	3	Erich Gamma , Richard Helm , Ralph Johnson , John Vlissides, Design patterns: elements of reusable object-oriented software, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1995
	4	Mark Grand, Patterns in Java, volume 1: a catalog of reusable design patterns illustrated with UML, John Wiley & Sons, Inc., New York, NY, 1998
	5	B. Heigl and M. Kowarschik. High-speed reconstruction for C-arm computed tomography. In Proceedings Fully 3D Meeting and HPIR Workshop, pages 25--28, Lindau, July 2007.
	6	T. G. Mattson, B. A. Sanders, and B. L. Massingill. Patterns for parallel programming. Addison-Wesley, 2005.
	7	D. Pham, S. Asano, M. Bolliger, M. Day, H. Hofstee, C. Johns, J. Kahle, A. Kameyama, J. Keaty, Y. Masubuchi, M. Riley, D. Shippy, D. Stasiak, M. Suzuoki, M. Wang, J. Warnock, S. Weitzel, D. Wendel, T. Yamazaki, and K. Yazawa. The design and implementation of a first-generation CELL processor. In IEEE Solid-State Circuits Conference, pages 184--185, San Francisco, 2005.
	8	E. J. Posnak, R. G. Lavender, and H. M. Vin. Adaptive pipeline: an object structural pattern for adaptive applications. In The 3rd Pattern Languages of Programming conference, Monticello, Illinois, September 1996.
	9	H. Scherl, S. Hoppe, F. Dennerlein, G. Lauritsch, W. Eckert, M. Kowarschik, and J. Hornegger. On-the-fly reconstruction in exact cone-beam CT using the Cell Broadband Engine Architecture. In Proceedings Fully 3D Meeting and HPIR Workshop, pages 29--32, Lindau, July 2007.
	10	H. Scherl, B. Keck, M. Kowarschik, and J. Hornegger. Fast GPU-based CT reconstruction using the Common Unified Device Architecture (CUDA). In Medical Imaging Conference, Honolulu, November 2007.
	11	H. Scherl, M. Koerner, H. Hofmann, W. Eckert, M. Kowarschik, and J. Hornegger. Implementation of the FDK algorithm for cone-beam CT on the Cell Broadband Engine Architecture. In J. Hsieh and M. Flynn, editors, Proceedings of SPIE Medical Imaging 2007: Physics of Medical Imaging, volume 6510, page 651058, San Diego, February 2007.
	12	A. Vermeulen, G. Beged-Dov, and P. Thompson. The pipeline design pattern. In OOPSLA?95 Workshop on Design Patterns for Concurrent, Parallel and Distributed Object-Oriented Systems, October 1995.
	13	K. Wiesent, K. Barth, N. Navab, P. Durlak, T. Brunner, O. Schuetz, and W. Seissler. Enhanced 3-D-reconstruction algorithm for C-arm systems suitable for interventional procedures. IEEE Transactions on Medical Imaging, 19(5):391--403, 2000.
	14	M. Zellerhoff, B. Scholz, E.-P. Rührnschopf, and T. Brunner. Low contrast 3-D-reconstruction from C-arm data. In M. J. Flynn, editor, Proceedings of SPIE, volume 5745, pages 646--655, April 2005.