Complexity prediction of automatic image registration: a case study on motion-compensated DSA

Authors:
Rob Albers;Eric Suijs;Peter H. N. de With
Affiliations:
Eindhoven University of Technology, Eindhoven, The Netherlands and Philips Healthcare, Interventional X-Ray, Best, The Netherlands;Philips Healthcare, Interventional X-Ray, Best, The Netherlands;Eindhoven University of Technology, Eindhoven, The Netherlands and CycloMedia Technology, Waardenburg, The Netherlands
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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Abstract

Real-time video and Quality-of-Service aspects play an increasing role in the development of medical imaging systems. To avoid resource overload and to guarantee the throughput of dynamic applications, we present a method for complexity prediction of image registration and motion-compensation algorithms, which can have a highly dynamic nature at run-time. As a case study, we explore a medical imaging function to reduce motion-artifacts in X-ray Digital Subtraction Angiography(DSA). Complexity prediction is based on motion estimation, prior to the actual image registration. Experimental results show that it is possible to model a dynamic content-dependent processing task with a high accuracy (95%, standard deviation 5%), thereby facilitating a higher quality for remaining tasks and well defined options for QoS.