NDLI: A multicore based parallel image registration method

Content Provider	IEEE Xplore Digital Library
Author	Lin Yang Leiguang Gong Hong Zhang Nosher, J.L. Foran, D.J.
Copyright Year	2009
Description	Author affiliation: Center of Biomedical Imaging and Informatics, The Cancer Institute of New Jersey, UMDNJ-Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA (Lin Yang; Hong Zhang; Foran, D.J.) \|\| IBM T. J. Watson Research, Hawthorne, NY, 10532, USA (Leiguang Gong) \|\| Dept. of Radiology, UMDNJ-Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA (Nosher, J.L.)
Abstract	Image registration is a crucial step for many imageassisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform.
Starting Page	98
Ending Page	101
File Size	853421
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5334782
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multicore processing Image registration Partitioning algorithms Robustness USA Councils Biomedical imaging Clustering algorithms Biomedical informatics Cancer Radiology
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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