An optimal constrained linear inverse method for magnetic source imaging
- Lawrence Berkeley Lab., CA (United States)
The optimal constrained linear inverse method (OCLIM) is a new algorithm for magnetic source imaging that approximates an unknown continuous current distribution as a weighted sum of current sources in fixed positions, uses prior information about the expected source power density and measurement noise, and can be efficiently computed. It achieves the minimum possible mean square reconstruction error for any linear estimator and provides statistical confidence limits on the reconstructed source amplitudes. The minimum-norm least squares and weighted pseudoinverse methods are included as special cases. However, OCLIM can produce reconstruction artifacts if the true current distribution is inconsistent with the assumed priors.
- Research Organization:
- Lawrence Berkeley Lab., CA (United States); California Univ., Berkeley, CA (United States). Dept. of Electrical Engineering and Computer Sciences
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 10107649
- Report Number(s):
- LBL--34512-Summ.; CONF-9311114--4; ON: DE94004014
- Country of Publication:
- United States
- Language:
- English
Similar Records
Algorithms for biomagnetic source imaging with prior anatomical and physiological information
A weighted iterative algorithm for neuromagnetic imaging