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Evolutionary partial differential equations for biomedical image processing.

Alessandro Sarti·Karol Mikula·Fiorella Sgallari·Claudio Lamberti
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Abstract

We are presenting here a model for processing space-time image sequences and applying them to 3D echo-cardiography. The non-linear evolutionary equations filter the sequence with keeping space-time coherent structures. They have been developed using ideas of regularized Perona-Malik an-isotropic diffusion and geometrical diffusion of mean curvature flow type (Malladi-Sethian), combined with Galilean invariant movie multi-scale analysis of Alvarez et al. A discretization of space-time filtering equations by means of finite volume method is discussed in detail. Computational results in processing of 3D echo-cardiographic sequences obtained by rotational acquisition technique and by real-time 3D echo volumetrics acquisition technique are presented. Quantitative error estimation is also provided.

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AlgorithmsBiomedical TechnologyEchocardiography, Three-DimensionalImage Processing, Computer-AssistedNonlinear DynamicsJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.

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Alessandro Sarti, Karol Mikula, Fiorella Sgallari, Claudio Lamberti. 2002. Evolutionary partial differential equations for biomedical image processing.. https://doi.org/10.1016/s1532-0464(02)00502-6

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