Algorithms for biomagnetic source imaging with prior anatomical and physiological information
- Univ. of California, Berkeley, CA (United States). Dept. of Electrical Engineering and Computer Sciences
This dissertation derives a new method for estimating current source amplitudes in the brain and heart from external magnetic field measurements and prior knowledge about the probable source positions and amplitudes. The minimum mean square error estimator for the linear inverse problem with statistical prior information was derived and is called the optimal constrained linear inverse method (OCLIM). OCLIM includes as special cases the Shim-Cho weighted pseudoinverse and Wiener estimators but allows more general priors and thus reduces the reconstruction error. Efficient algorithms were developed to compute the OCLIM estimate for instantaneous or time series data. The method was tested in a simulated neuromagnetic imaging problem with five simultaneously active sources on a grid of 387 possible source locations; all five sources were resolved, even though the true sources were not exactly at the modeled source positions and the true source statistics differed from the assumed statistics.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Research (ER); National Science Foundation (NSF)
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 195677
- Report Number(s):
- LBL--38115; ON: DE96005811
- Country of Publication:
- United States
- Language:
- English
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