Current Density Reconstructions Using the L1 Norm
A major goal in biomagnetism is the reconstruction of current distributions without making preliminary assumptions about number and temporal properties of the sources to be reconstructed. We propose a new current density reconstruction method that computes source images with high resolution and small blurring. A nonlinear functional, the L1-norm, is used as a source constraint. The L1-norm is the sum of absolute current densities. A simple Simulation shows, that the L1-norm does neither impose artificial smoothness nor sharpness upon the reconstructed sources. We have implemented three different minimization schemes for the L1-norm, which we compare against each other and against the MNLS (minimum norm least squares, L2-norm) method . Unlike the L1-norm method described earlier , our approaches tolerate noisy data and arbitrary source orientations.
KeywordsSingle Dipole Reconstructed Source Simulated Source Source Configuration Magnetic Source Image
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- Fuchs, M., Wagner, M., Wischmann, H.-A., Generalized minimum norm least squares reconstruction algorithms, ISBET Newsletter (ISSN 0947–5133), 1994, (5):8-l 1.Google Scholar
- Wagner, M., Fuchs, M., Wischmann, H:-A., Ottenberg, K., Dössel, O., Cortex segmentation from 3D MR images for MEG reconstructions, In: C. Baumgartner et al, Biomagnetism: fundamental research and clinical applications, Amsterdam, Elsevier/IOS Press, 1995, 433–438.Google Scholar
- Kuenzi, H.P., Tzschach, H.G., Zehnder, C.A., Numerical methods of mathematical optimization, New York, Academic Press, 1971.Google Scholar