GPU accelerated non-rigid registration for the evaluation of cardiac function

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Abstract

We present a method for the fast and efficient tracking of motion in cardiac magnetic resonance (CMR) cines. A GPU accelerated Levenberg-Marquardt non-linear least squares optimization procedure for finite element non-rigid registration was implemented on an NVIDIA graphics card using the OpenGL environment. Points were tracked from frame to frame using forward and backward incremental registration. The inner (endocardial) and outer (epicardial) boarders of the heart were tracked in six short axis cines with ∼25 frames through the cardiac cycle in 36 patients with vascular disease. Contours placed by two independent expert observers using a semi-automatic ventricular analysis program (CIM version 4.6) were used as the gold standard. The method took 0.5 seconds per frame, and the maximum Hausdorff errors were less than 2 mm on average which was of the same order as the expert inter-observer error. In conclusion, GPU accelerated Levenberg-Marquardt non-linear optimization enables fast and accurate tracking of cardiac motion in CMR images. © 2008 Springer Berlin Heidelberg.

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APA

Li, B., Young, A. A., & Cowan, B. R. (2008). GPU accelerated non-rigid registration for the evaluation of cardiac function. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5242 LNCS, pp. 880–887). Springer Verlag. https://doi.org/10.1007/978-3-540-85990-1_106

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