With the harmonisation of data requirements for pesticide registration under EC Directive 91/414 there is need for progress on the techniques used to analyse such data and so help make consistent the judgements applied by national regulatory authorities. This paper proposes a Bayesian technique for
A high performance computing approach to the registration of medical imaging data
β Scribed by Simon K. Warfield; Ferenc A. Jolesz; Ron Kikinis
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 750 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0167-8191
No coin nor oath required. For personal study only.
β¦ Synopsis
A novel automatic registration algorithm for the alignment of medical imaging data was developed. The algorithm measures alignment by comparison of dense feature sets (tissue labels) and optimum alignment is found by minimizing the mismatch of tissue segmentations. A parallel implementation that distributes resampling and comparison operations across a cluster of symmetric multiprocessors achieves execution times in a clinically compatible range (5Β±10 min). Each node executes a parallelized resample and compare operation implemented with POSIX threads, and work is dynamically load balanced across the cluster with communication implemented with MPI. The quality of the registration algorithm and the performance characteristics of the parallel implementation were investigated for typical registration problems. The algorithm has been used to successfully achieve intrapatient and interpatient registration of tissue segmentations without any manual intervention for over three hundred scans of the brain.
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