An analytical method for reconstruction of biological objects from discrete noisy data

Peter Dabnichki and Angel Zhivkov

Mathematical and Computer Modelling of Dynamical Systems, 2010, vol. 16, issue 5, 431-442

Abstract: The work represents a stage in the development of an integrated process for the analysis of biological objects -- analytical image reconstruction from noisy data that allows fast dynamical analysis. The method also provides an interface to discrete methods such as finite element method (FEM). Two different methods are proposed -- one is based on theta functions and the other uses analytical ellipsoids. Both methods possess built-in ability to remove noise from experimental measurements. The methods also have significant advantages if used in biological applications as it could process data directly from optical or general image devices such as cameras, microscopes and scans. Real-time online reconstruction and relevant computational analysis could be performed due to the rapid computational speed which in turn provides a good opportunity for the development of an integrated medical diagnostics technology. Both methods are demonstrated using appropriate examples.

Date: 2010
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DOI: 10.1080/13873954.2010.507101

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