Omega-space adaptive acquisition technique for magnetic resonance imaging from projections

Maximally spaced projection sequencing in electron paramagnetic resonance imaging

Electron paramagnetic resonance imaging (EPRI) provides 3D images of absolute oxygen concentration (pO₂) in vivo with excellent spatial and pO₂ resolution. When investigating such physiologic parameters in living animals, the situation is inherently dynamic. Improvements in temporal resolution and experimental versatility are necessary to properly study such a system. Uniformly distributed projections result in efficient use of data for image reconstruction. This has dictated current methods such as equal-solid-angle (ESA) spacing of projections. However, acquisition sequencing must still be optimized to achieve uniformity throughout imaging. An object-independent method for uniform acquisition of projections, using the ESA uniform distribution for the final set of projections, is presented. Each successive projection maximizes the distance in the gradient space between itself and prior projections. This maximally spaced projection sequencing (MSPS) method improves image quality for intermediate images reconstructed from incomplete projection sets, enabling useful real-time reconstruction. This method also provides improved experimental versatility, reduced artifacts, and the ability to adjust temporal resolution post factum to best fit the data and its application. The MSPS method in EPRI provides the improvements necessary to more appropriately study a dynamic system.

Adaptive compression algorithm from projections: application on medical greyscale images

Image compression plays a crucial role in medical imaging, allowing efficient manipulation, storage, and transmission of binary, grey-scale, or colour images. Nevertheless, in medical applications the need to conserve the diagnostic validity of the image requires the use of lossless compression methods, producing low compression factors. In this paper, a novel near-lossless compression algorithm from projections, which almost eliminates both redundant information and noise from a greyscale image while retaining all relevant structures and producing high compression factors, is proposed. The algorithm is tested on experimental medical greyscale images from different modalities and different body districts and results are reported.

SNR phase order k-space encoding (SPOKE)

A method of determining the phase-encode order for MR Fourier-encoded imaging is described, which provides an additional option for optimizing images from samples with signals that change during data acquisition. Examples are in hyperpolarized helium gas imaging of the lungs where polarization is lost with each RF pulse or the signal changes observed in rapid dynamic studies with T(1) or T(2)* contrast agents when mixing is taking place. The method uses a single frequency-encoded projection in the proposed phase-encoding direction. The projection is subsequently sorted into signal-to-noise ratio (SNR) order. The indices of the sorted array are then used to create the phase-encode table to be used for the scan. This phase table is sorted in descending SNR order for signals that decrease during data acquisition and in ascending order for signals that increase during data acquisition. Simulations suggest that this technique can produce higher resolution than centric-ordered phase encoding at the expense of increased modulation (ghosting) artifact for dynamically changing signals. Initial practical implementation of the technique has been carried out on a dedicated 0.2-T Niche MR system, and the test object results agree well with simulations. Hyperpolarized 3-He lung images have also been acquired and postprocessed using the SNR phase order k-space encoding (SPOKE) methodology and show potential for improved imaging with high flip angles where polarization is rapidly lost. Applications may also be found for 3D volumetric acquisitions where two dimensions can be SPOKE encoded.