Abstract: 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?) 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.

Abstract: The present invention relates to a method and system for distributed computing an S transform dataset of multidimensional image data of an object. The multidimensional image data are fast Fourier transformed into Fourier domain producing a Fourier spectrum. The respective Fourier frequencies are then partitioned into a plurality of portions of frequencies for simultaneously processing. Processing of each of the plurality of portions of the Fourier frequencies is assigned to a respective processor of a plurality of processors. The Fourier spectrum of multidimensional image data and each of the plurality of portions of the Fourier frequencies is transmitted to the respective processor. The portions of the Fourier frequencies are then simultaneously processed in order to produce the S transform dataset. The S transform data are then collected and stored.

Abstract: 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?) 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.

Abstract: The present invention relates to a method and system for enhancing resolution of a magnetic resonance image of an object. The method combines information from a plurality of low-resolution images with a Field Of View shifted by a distance less than a pixel width to create a synthesized image having substantially improved image quality. Information from the low-resolution images is merged and application of an aperture function enhances the SNR of the synthesized image resulting in synthesized images having a substantially higher spatial resolution as well as a substantially increased SNR. The method and system for enhancing resolution of a magnetic resonance image is highly beneficial for a MRI practitioner by substantially improving image quality, thus facilitating diagnostic methods such as texture analysis and disease specific tissue segmentation.

Abstract: 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.