The Development and Application of Calculated Readout in Spectral Parallelism in Magnetic Resonance Imaging

In magnetic resonance imaging (MRI), an object within a field-of-view (FOV) is spatially encoded with a broad spectrum of frequency components generating signals that decohere with one another to create a decaying echo with a large peak amplitude. The echo is short and decays at a rapid rate relative to the readout period when performing high resolution imaging of a sizable object where many frequency components are encoded resulting in faster decoherence of the generated signals. This makes it more difficult to resolve fine details as the echo quickly decays down to the quantization limit. Samples collected away from the peak signal, which are required to produce high resolution images, have very low amplitudes and therefore, poor dynamic range. We propose a novel data acquisition system, Calculated Readout in Spectral Parallelism (CRISP), that spectrally separates the radio frequency (RF) signal into multiple narrowband channels before digitization. The frequency bandwidth of each channel is smaller than the FOV and centered over a part of the image with minimal overlap with the other channels. The power of the corresponding temporal signal in each channel is reduced and spread across a broader region in time with a slower decay rate. This allows the signal from each channel to be independently amplified such that a larger portion of the signal is digitized at higher bits. Therefore, the dynamic range of the signal is improved and sensitivity to quantization noise is reduced. We present a realization of CRISP using inexpensive analog filters and preliminary results from high resolution images.