Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Mechanical measurement system
Reexamination Certificate
2006-08-01
2006-08-01
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Mechanical measurement system
C702S115000, C702S191000, C382S145000, C324S301000
Reexamination Certificate
active
07085656
ABSTRACT:
A technique for eliminating edge artifacts in magnetic microscopy includes the steps of scanning a SQUID over an object under study to acquire values of magnetic fields produced by currents running in the object to create a first data set having N data points. At the end of the first data set, N zero data points are added to create a second data set having 2N data points. Fast Fourier Transform (FFT) is further applied to the 2N data set to obtain k-space having b(k) values. The b(k) values of the k-space are averaged, and the averaged b(k) values corresponding to k exceeding a predetermined k value are filtered off. A set of current density representations i(k) in the k-space are obtained to which inverse FFT is applied to obtain a map of current densities I(x,y) of the object. A system for performing the method of the present invention includes a software designed to suppress (or eliminate) edge artifacts present in the obtained images.
REFERENCES:
patent: 6571183 (2003-05-01), Wellstood et al.
Busko Claudio Felipe
Matthews John
Wellstood Frederick Charles
Barlow John
Rosenberg , Klein & Lee
University of Maryland
Walling Meagan S
LandOfFree
Method for suppressing edge artifacts in magnetic microscopy does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method for suppressing edge artifacts in magnetic microscopy, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method for suppressing edge artifacts in magnetic microscopy will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3625248