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Proceedings Paper

Edge-preserving MAP estimation of motion vector fields in noisy low-dose x-ray image sequences
Author(s): Til Aach
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Paper Abstract

We describe a motion compensated temporally recursive noise reduction technique especially suited for sequences of moving X-ray images, where we focus on a robust motion estimator which is able to deal with the high noise levels in such images. These noise levels are caused by the very low X-ray dose rates used in medical real-time imaging (quantum-limited imaging). The robustness of our motion estimator is achieved by spatiotemporal regularization using a generalized Gauss-Markov random field. Unlike quadratic regularization by Gauss-Markov random fields, generalized Gauss-Markov random fields are able to account for motion edges without the need to explicitly specify an detection threshold. Instead, our model controls edges by a `soft' parameter, which gradually allows the regularization term to behave like a median filter, which preserves edges without using detection thresholds.

Paper Details

Date Published: 1 October 1998
PDF: 10 pages
Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); doi: 10.1117/12.323215
Show Author Affiliations
Til Aach, Medical Univ. of Luebeck (Germany)

Published in SPIE Proceedings Vol. 3460:
Applications of Digital Image Processing XXI
Andrew G. Tescher, Editor(s)

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