Paper
1 May 1994 Dynamic 3D reconstructions of the heart wall from tomographic imaging
Joerg Lange, Alexander von Smekal
Author Affiliations +
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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joerg Lange and Alexander von Smekal "Dynamic 3D reconstructions of the heart wall from tomographic imaging", Proc. SPIE 2168, Medical Imaging 1994: Physiology and Function from Multidimensional Images, (1 May 1994); https://doi.org/10.1117/12.174389
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KEYWORDS
Heart

Image segmentation

Neurons

Visualization

Data acquisition

Tomography

Magnetic resonance imaging

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