Tait, Roger J., Schaefer, Gerald, Hopgood, Adrian A. and Zhu, Shao Ying (2006) Efficient 3-D Medical Image Registration Using a Distributed Blackboard Architecture. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, pp. 3045-3048

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Abstract

A major drawback of 3-D medical image registration techniques is the performance bottleneck associated with re-sampling and similarity computation. Such bottlenecks limit registration applications in clinical situations where fast execution times are required and become particularly apparent in the case of registering 3-D data sets. In this paper a novel framework for high performance intensity-based volume registration is presented. Geometric alignment of both reference and sensed volume sets is achieved through a combination of scaling, translation, and rotation. Crucially, resampling and similarity computation is performed intelligently by a set of knowledge sources. The knowledge sources work in parallel and communicate with each other by means of a distributed blackboard architecture. Partitioning of the blackboard is used to balance communication and processing workloads. Large-scale registrations with substantial speedups, when compared with a conventional implementation, have been demonstrated

Item Type:	Book Section
Status:	Published
DOI:	10.1109/IEMBS.2006.260146
School/Department:	School of Science, Technology and Health
URI:	https://ray.yorksj.ac.uk/id/eprint/9959

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