976076 Alberta Inc.

Robert Brown

Hongmei Zhu

J Ross Mitchell

T Chen Fong

Bradley G Goodyear

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. The method and system for computing the S transform according to the invention provides a substantially increased computation speed enabling use of the S transform for practical applications in a clinical setting.

Distributed vector processing of the S transform for medical applications

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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Spirit River, Canada

Robert Brown