976076 Alberta Inc.

Calgary Scientific Inc.

Bradley G Goodyear

Hongmei Zhu

J Ross Mitchell

T Chen Fong

Robert Brown

The present invention relates to a method for filtering time-varying MR signal data prior to image reconstruction. A one-dimensional FT is applied to the time-varying MR signal data along each frequency-encode line of k space. The phase p of each complex pair (R,I) of the FT transformed data is calculated to create a phase profile for each frequency-encode line. This process is repeated for all time points of the time-varying MR signal data. The time course of each point within the phase profile is then transformed into Stockwell domain producing ST spectra. Frequency component magnitudes indicative of an artifact are determined and replaced with a predetermined frequency component magnitude. Each of the ST spectra is then collapsed into a one-dimensional function. New real and imaginary values (R',I&#x2032;) of the complex Fourier data are calculated based on the collapsed ST spectra which are transformed using one-dimensional inverse Fourier transformation for producing filtered time-varying MR signal data. The method for filtering time-varying MR signal data is highly advantageous by easily identifying high-frequency artifacts within the ST spectrum and filtering only frequency components near the artifacts. Therefore, high-frequency artifacts are substantially removed while the frequency content of the remaining signal is preserved, enabling for example detection of subtle frequency changes occurring over time.

Filtering artifact from fMRI data using the stockwell transform

The present invention relates to a method for filtering time-varying MR signal data prior to image reconstruction. A one-dimensional FT is applied to the time-varying MR signal data along each frequency-encode line of k space. The phase p of each complex pair (R, I) of the FT transformed data is calculated to create a phase profile for each frequency-encode line. This process is repeated for all time points of the time-varying MR signal data. The time course of each point within the phase profile is then transformed into Stockwell domain producing ST spectra. Frequency component magnitudes indicative of an artifact are determined and replaced with a predetermined frequency component magnitude. Each of the ST spectra is then collapsed into a one-dimensional function. New real and imaginary values (R', I&#x2032;) of the complex Fourier data are calculated based on the collapsed ST spectra which are transformed using one-dimensional inverse Fourier transformation for producing filtered time-varying MR signal data. The method for filtering time-varying MR signal data is highly advantageous by easily identifying high-frequency artifacts within the ST spectrum and filtering only frequency components near the artifacts. Therefore, high-frequency artifacts are substantially removed while the frequency content of the remaining signal is preserved, enabling for example detection of subtle frequency changes occurring over time.

The present invention relates to a method for processing magnetic resonance signal data. magnetic resonance signal data in dependence upon a magnetic resonance signal time series are received. The magnetic resonance signal data are then transformed into a time-frequency Stockwell domain using a localizing time window having a frequency dependent window width in order to provide multi-resolution in the time-frequency domain. The Stockwell transformed magnetic resonance signal data are then processed in the Stockwell domain, for example, filtered based on time-frequency information of the Stockwell transformed magnetic resonance signal data. The processed Stockwell transformed magnetic resonance signal data are then transformed into Fourier domain by summing the Stockwell transformed magnetic resonance signal data over time indices of the Stockwell domain. In a further step the Fourier transformed magnetic resonance signal data are then transformed into time domain using inverse Fourier transformation. In another embodiment the method for processing magnetic resonance signals is extended for processing two-dimensional magnetic resonance signal image data in a space-frequency Stockwell domain. The method for processing magnetic resonance signals according to the invention using the Stockwell transform overcomes many limitations of the Fourier framework of existing magnetic resonance signal processing tools. It is highly advantageous by providing frequency and time/space information while keeping a close connection with the Fourier formalism, which allows implementation of the method according to the present invention into existing Fourier-based signal processing tools.

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Calgary, Canada

Bradley G Goodyear