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Proceedings Paper

Dynamic 3D reconstructions of the heart wall from tomographic imaging
Author(s): Joerg Lange; Alexander von Smekal
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Paper Abstract

We present a dynamic reconstruction of the left ventricle (LV) of the human heart. LV surface is represented by a set of points. The coordinates of these points are iterated by an artificial neural network while optimizing the match between the reconstruction based on these coordinates and the signal data. The input for the network are the segment's positions which represent the surface within the original data. The output is a set of real-valued coordinates quantifying the location of the LV surface points. The reconstruction is simultaneously developed in 3-D space and temporal domain. A topological constraint during training of the network gives corresponding vertices in space and time with global correctness. At any phase of the heart beat the network develops a map among the surface points which is highly ordered. This results in very regular wire-frames, that can be displayed rapidly on even small graphic workstations. Without time and third dimension this is very similar to Durbin's algorithm for solving the traveling salesman problem (TSP). To achieve a smooth representation we keep our network from developing the full TSP optimal solution.

Paper Details

Date Published: 1 May 1994
PDF: 8 pages
Proc. SPIE 2168, Medical Imaging 1994: Physiology and Function from Multidimensional Images, (1 May 1994);
Show Author Affiliations
Joerg Lange, Scientific Visualization Group of HLRZ (Germany)
Alexander von Smekal, Clinic Grosshadern (Germany)

Published in SPIE Proceedings Vol. 2168:
Medical Imaging 1994: Physiology and Function from Multidimensional Images
Eric A. Hoffman; Raj S. Acharya, Editor(s)

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