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Biomedical subjects

Pablo Irarrazaval

Publications and source records attributed to Pablo Irarrazaval.

3 recordsLinked to original sources

Off-resonance correction using an estimated linear time map.

Images acquired in the presence of magnetic field deviations and reconstructed without taking into account the off-resonance, are distorted and corrupted with artifacts. Several post-processing algorithms have been developed for correcting the distortion when it is not possible to fix the field inhomogeneities. These off-resonance correction methods are, in general, slow and computing intensive. To make them faster they are usually adapted to a particular situation or approximated. One of these approximations is to assume that the field map is linear. Although this assumption makes the algorithm fast and robust it is not well suited for arbitrary field maps. On the other hand, there are k-space trajectories with an almost linear time map (time at which each k-space value is acquired), such as 2DFT and EPI. This paper presents an algorithm for off-resonance correction based on a linear time map approximation. This approximation allows a fast algorithm that takes advantage of the almost linearity of the time map and uses the whole field map to correct the images. The proposed correction algorithm reduces the off-resonance induced artifacts while being fast. The linear approximation of the time map needs to be done only once for each trajectory because it does not depend on the acquired image or field map data. The method can also be extended to a multi-plane approximation for sequences with more complex time maps.

Algorithms↗

A correction algorithm for undersampled images using dynamic segmentation and entropy based focus criterion.

A post-processing technique is presented for correcting images undersampled in k-space. The method works by taking advantage of the image's background zeros (dynamically segmented through the application of a threshold) to extrapolate the missing k-space samples. The algorithm can produce good quality images from a small set of k-space frequencies with only a few iterations of simple matrix operations, using the image entropy as the focus criterion. It does not require any special patient preparation, extra pulse sequences, complex gradient programming or specialized hardware. This makes it a good candidate for any application that requires short scan times or where only few frequencies can be sampled.

Algorithms↗

MRI fast tree log scanning with helical undersampled projection acquisitions.

Magnetic Resonance Imaging opens an alternative way to analyze wood structures using a non-destructive technology. It provides high resolution, compound-based contrast manipulation and increased data acquisition flexibility. The technique is particularly useful for tree logs, since they present several characteristics that can be used to reduce the long scan time. This study proposes a method that takes advantage of the log cylindrical symmetry, acquiring transverse 1-D projections with a helical and undersampled pattern. Linear interpolation is used to estimate the skipped data and slice images are reconstructed by filtered backprojection. The sequence is improved using selective multi-pass scanning, without major variations of the scan time. Computer simulations and experimental results show that the proposed technique can increase the scan speed by a factor of 6, while maintaining the ability to identify typical tree log characteristics.

Computer Simulation↗