Electricity: measuring and testing – Particle precession resonance – Spectrometer components
Reexamination Certificate
2001-08-22
2003-10-14
Gutierrez, Diego (Department: 2859)
Electricity: measuring and testing
Particle precession resonance
Spectrometer components
C324S309000
Reexamination Certificate
active
06633162
ABSTRACT:
BACKGROUND OF THE DISCLOSURE
The present specification relates to filtering frequency encoded imaging signals. More particularly, the present specification relates to filtering magnetic resonance imaging (MRI) signals.
In MRI systems, radio frequency (RF) signals are used in conjunction with magnetic fields to image areas of a patient. MRI measurements are divided into a period of RF excitation and a period of signal emission and acquisition. These measurements are performed in a cyclic manner in which the MRI measurement is repeated many times to accumulate different data during each cycle or to make the same measurement at different locations in the subject. A wide variety of preparative excitation techniques are known which involve the application of one or more RF excitation pulses of varying magnitude, frequency content, phase and duration. Such RF excitation pulses may have a narrow frequency spectrum (selective excitation pulse), or they may have a broad frequency spectrum (nonselective excitation pulse) which can produce transverse magnetization over a range of resonant frequencies. The prior art is replete with RF excitation techniques that are designed to take advantage of particular MRI phenomena.
After an excitation pulse, the MRI system receives the RF signals emitted by the excited nuclei and uses these signals to construct an image of the patient. The received signals containing image information lie in a band of frequencies centered at the Larmor frequency. Before the image information can be extracted to construct an image of the patient (e.g., via Fast Fourier Transform or FFT), these signals are demodulated by shifting the frequencies of the signals to lower frequencies to improve the efficiency of the FFT. Conventional signal conversion is employed to shift the band of frequencies by mixing the image information signal with a reference signal. Unless properly filtered out, noise in a band of frequencies that is symmetrical about the reference signal frequency with the image information band will become superimposed onto the image information in the resultant signal produced by the heterodyning.
This problem can be avoided if quadrature receivers are used to bring the image information to baseband. The use of in-phase (I) and quadrature (Q) demodulation allows frequencies on either side of a reference frequency to be distinguished, if the phase and amplitude adjustment of the I and Q signal channels is exact.
From a noise immunity standpoint, it is advantageous to convert the image information signal into the digital domain as early in the processing as possible. Resampling or decimation of the MR data yields further improvements in the computational efficiency of the FFT's which is accomplished by digitally filtering the MR data to the frequency range of interest. Once filtered, the data set can be reduced by an amount proportional to the decreased bandwidth. For example, if the MR data has an initial bandwidth of 64 kHz and it is filtered to a bandwidth of 32 kHz, every other data point can be discarded, which corresponds to a proportional resampling factor of ½. One drawback of this simple downsampling approach is that proportional resamplings are limited to resampling factors having a numerator (i.e., upsampling factor) of one. Since the resampling factor determines the resolution at which the image can be displayed, what is needed is a system that provides additional flexibility in the resampling factor.
Accordingly, what is needed is an improved system and method for filtering frequency encoded imaging signals that allows resampling by substantially any rational, fractional resampling factor, including resampling factors having upsampling factors other than one. Further still, what is needed is a system and method for filtering frequency encoded imaging signals that provides resampling by substantially any rational, fractional resampling factor in the time domain. Further still, what is needed is a digital filter for filtering frequency encoded imaging signals that applies filter coefficients to MRI data in a more efficient manner. Further yet, what is needed is a system and method for filtering frequency encoded imaging signals that allows processing of a wider bandwidth signal, having more filter taps, which will in turn improve MR image quality. Further still, what is needed is a system and method for filtering frequency encoded imaging signals that provides more efficient sampling of the region of interest, improves resolution of the area of interest, provides full flexibility of filter bandwidth selection, and provides efficient reconstruction of critically sampled data by minimizing the computation required by the FFT reconstruction.
The teachings hereinbelow extend to those embodiments which fall within the scope of the appended claims, regardless of whether they accomplish one or more of the above-mentioned needs.
SUMMARY OF EXEMPLARY EMBODIMENTS
According to one exemplary embodiment, a method of filtering frequency encoded imaging signals includes receiving the frequency encoded imaging signals in the time domain and demodulating the frequency encoded imaging signals. The method further includes upsampling the frequency encoded imaging signals by an integer upsampling factor, reducing the bandwidth of the frequency encoded imaging signals, and downsampling the frequency encoded imaging signals by an integer downsampling factor. The frequency encoded imaging signals are resampled by a rational resampling factor substantially equal to the integer upsampling factor divided by the integer downsampling factor.
According to another exemplary embodiment, a digital filter for filtering magnetic resonance imaging (MRI) signals includes a quadrature demodulator, a filter, and a resampler. The quadrature demodulator is configured to receive the MRI signals and to demodulate the MRI signals. The filter is configured to reduce the bandwidth of the MRI signals. The resampler is configured to receive the MRI signals and to resample the MRI signals. The resampler operates in the time domain and is configured to resample the MRI signals based on a selected one of a plurality of fractional resampling factors having different upsampling integer factors.
According to yet another exemplary embodiment, a method of filtering frequency encoded imaging signals includes resampling the imaging signals by an integer upsampling factor (L) and an integer downsampling factor (M) and applying filter coefficients to the imaging signals to generate output signals having a reduced bandwidth. A first subset of the filter coefficients is applied to the imaging signals to generate a first output signal and a second subset of the filter coefficients is applied to the imaging signals to generate a second output signal.
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Ronald E. Crochiere et al., Multirate Digital Signal Processing, pp. 13-126.
Gilling Chris J.
Kreger Kevin Scott
Zhang James Nengjie
Della Penna Michael A.
GE Medical Systems Global Technology Company LLC
Gutierrez Diego
Vargas Dixomara
Vogel Peter J.
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