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Proceedings Paper

Kalman filter technique applied to surface reconstruction and visualization from noisy volume data
Author(s): Raul San Jose Estepar; Alberto Rivera; Marco Pinacho; Carlos Alberola-Lopez; Juan Ruiz
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Paper Abstract

In this paper we propose a low-cost computational method applied to the smoothing of surfaces reconstructed from noisy data, as it is typically the case in ultrasound imaging. It makes use of tracking ideas. Our method is, to our knowledge, a novel and competitive alternative to those which make use of traditional methods of optical flow for the smoothing of the normals of an object's surfaces. Those methods, as it is well- known, are very involved in calculations. Our method is based on a Kalman filter; we propose a stochastic dynamic model which exploits the spatial coherence present in the data. We end up having more efficient computational scheme with performance close to the optical flow method. A provision is made to impede the filter to diverge when the data depart from the assumed model. Our results both with synthetic and real volume data show that our proposal is realistic in terms of rendering: a good trade off between computational resources and graphical results seem to be achieved.

Paper Details

Date Published: 12 April 2000
PDF: 12 pages
Proc. SPIE 3982, Medical Imaging 2000: Ultrasonic Imaging and Signal Processing, (12 April 2000); doi: 10.1117/12.382255
Show Author Affiliations
Raul San Jose Estepar, ETSI Telecomunicacion (Spain)
Alberto Rivera, ETSI Telecomunicacion (Spain)
Marco Pinacho, ETSI Telecomunicacion (Spain)
Carlos Alberola-Lopez, ETSI Telecomunicacion (Spain)
Juan Ruiz, ETSI Telecomunicacion (Spain)


Published in SPIE Proceedings Vol. 3982:
Medical Imaging 2000: Ultrasonic Imaging and Signal Processing
K. Kirk Shung; Michael F. Insana, Editor(s)

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