Purpose Nyquist ghost artifacts in echo planar imaging (EPI) are originated from phase mismatch between the even and odd echoes. However, conventional correction methods using reference scans often produce erroneous results especially in high‐field MRI due to the nonlinear and time‐varying local magnetic field changes. Recently, it was shown that the problem of ghost correction can be reformulated as k‐space interpolation problem that can be solved using structured low‐rank Hankel matrix approaches. Another recent work showed that data driven Hankel matrix decomposition can be reformulated to exhibit similar structures as deep convolutional neural network. By synergistically combining these findings, we propose a k‐space deep learning approach that immediately corrects the phase mismatch without a reference scan in both accelerated and non‐accelerated EPI acquisitions. Theory and Methods To take advantage of the even and odd‐phase directional redundancy, the k‐space data are divided into 2 channels configured with even and odd phase encodings. The redundancies between coils are also exploited by stacking the multi‐coil k‐space data into additional input channels. Then, our k‐space ghost correction network is trained to learn the interpolation kernel to estimate the missing virtual k‐space data. For the accelerated EPI data, the same neural network is trained to directly estimate the interpolation kernels for missing k‐space data from both ghost and subsampling. Results Reconstruction results using 3T and 7T in vivo data showed that the proposed method outperformed the image quality compared to the existing methods, and the computing time is much faster. Conclusions The proposed k‐space deep learning for EPI ghost correction is highly robust and fast, and can be combined with acceleration, so that it can be used as a promising correction tool for high‐field MRI without changing the current acquisition protocol.
While the perception of stickiness serves as one of the fundamental dimensions for tactile sensation, little has been elucidated about the stickiness sensation and its neural correlates. The present study investigated how the human brain responds to perceived tactile sticky stimuli using functional magnetic resonance imaging (fMRI). To evoke tactile perception of stickiness with multiple intensities, we generated silicone stimuli with varying catalyst ratios. Also, an acrylic sham stimulus was prepared to present a condition with no sticky sensation. From the two psychophysics experiments–the methods of constant stimuli and the magnitude estimation—we could classify the silicone stimuli into two groups according to whether a sticky perception was evoked: the Supra-threshold group that evoked sticky perception and the Infra-threshold group that did not. In the Supra-threshold vs. Sham contrast analysis of the fMRI data using the general linear model (GLM), the contralateral primary somatosensory area (S1) and ipsilateral dorsolateral prefrontal cortex (DLPFC) showed significant activations in subjects, whereas no significant result was found in the Infra-threshold vs. Sham contrast. This result indicates that the perception of stickiness not only activates the somatosensory cortex, but also possibly induces higher cognitive processes. Also, the Supra- vs. Infra-threshold contrast analysis revealed significant activations in several subcortical regions, including the pallidum, putamen, caudate and thalamus, as well as in another region spanning the insula and temporal cortices. These brain regions, previously known to be related to tactile discrimination, may subserve the discrimination of different intensities of tactile stickiness. The present study unveils the human neural correlates of the tactile perception of stickiness and may contribute to broadening the understanding of neural mechanisms associated with tactile perception.
Purpose:To propose a novel 3D ultrafast gradient echo-based MRI method, dubbed RASE, using quadratic-phase encoding. Theory and Methods: Several characteristics of RASE, including spin behaviors, spatial resolution, SNR, and reduction of susceptibility-induced signal loss, were analytically described. A way of compensating for TE variation was suggested in the quadratic phase-encoding direction. Lemon, in vivo rat and mouse images were demonstrated at 9.4T, including a feasibility study for DCE-MRI as one of promising applications.Results: RASE was successfully demonstrated by lemon and in vivo rat brain imaging, showing a good robustness to field inhomogeneity. Contribution of the quadratic phase to signal enhancement in a range of magnetic susceptibilities was also evaluated by simulation. Taking a geometric mean of 2 phantom data acquired with opposite gradient polarities effectively compensated for the effect of TE variation.Preliminary DCE-MRI results were also presented, showing that RASE could more accurately estimate Gd concentration than FLASH. Conclusion: RASE offers a shorter effective TE, having less sensitivity to field inhomogeneity and T 2 * effects, much less Nyquist ghosting or chemical-shift artifacts than gradient echo EPI (GE-EPI). We highly anticipate that RASE can be an alternative to GE-EPI in many applications, particularly those requiring high spatial and temporal resolutions in a broad volume coverage.
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