Journal article
On developing B-spline registration algorithms for multi-core processors
Physics in medicine & biology, v 55(21), pp 6329-6351
07 Nov 2010
PMID: 20938071
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Spline-based deformable registration methods are quite popular within the medical-imaging community due to their flexibility and robustness. However, they require a large amount of computing time to obtain adequate results. This paper makes two contributions towards accelerating B-spline-based registration. First, we propose a grid-alignment scheme and associated data structures that greatly reduce the complexity of the registration algorithm. Based on this grid-alignment scheme, we then develop highly data parallel designs for B-spline registration within the stream-processing model, suitable for implementation on multi-core processors such as graphics processing units (GPUs). Particular attention is focused on an optimal method for performing analytic gradient computations in a data parallel fashion. CPU and GPU versions are validated for execution time and registration quality. Performance results on large images show that our GPU algorithm achieves a speedup of 15 times over the single-threaded CPU implementation whereas our multi-core CPU algorithm achieves a speedup of 8 times over the single-threaded implementation. The CPU and GPU versions achieve near-identical registration quality in terms of RMS differences between the generated vector fields.
Metrics
Details
- Title
- On developing B-spline registration algorithms for multi-core processors
- Creators
- J A Shackleford - Electrical and Computer Engineering Department, Drexel University, Philadelphia, PA 19104, USAN KandasamyG C Sharp
- Publication Details
- Physics in medicine & biology, v 55(21), pp 6329-6351
- Publisher
- Institute of Physics (IOP); England
- Grant note
- C06CA059267 / NCI NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000283056000004
- Scopus ID
- 2-s2.0-78149325717
- Other Identifier
- 991014878219004721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Biomedical
- Radiology, Nuclear Medicine & Medical Imaging