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S-wave seismic imaging of near-surface sediments using tailored processing strategies
Reflection seismic imaging using horizontally-polarized S-waves (SH) can increase resolution and it could be cost-efficient compared to the common use of P-waves. However, since S-wave application often delivers varying data quality, appropriate processing schemes are required for particular imaging and interpretation purposes. In this paper, we present four tailored processing strategies that are applied to SH-wave data acquired in an overdeepened Quaternary basin in the Alpine foreland, the Tannwald Basin. The applied processing schemes consist of (1) processing using a short automatic gain control window that enhances structural details and highlights small-scale structures, (2) offset restriction indicating that relative small offsets are sufficient for adequate imaging, which offers reduced field operation costs, (3) coherency-enhancement that reveals large-scale structures for interpretation, and (4) adapted amplitude scaling that enables structural comparison of P-wave and S-wave seismic sections. With respect to P-wave data measured on the same profile, we demonstrate the benefits of the S-wave seismic reflection method. P-waves offer robust imaging results, but S-waves double the resolution, better depict shallow reflections, and may image reflectors in areas where the P-wave struggles. At least for the Tannwald Basin, S-wave imaging is also more cost-efficient than P-wave imaging. © 2020 The Authors
High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing
Diffusion Kurtosis Imaging (DKI) is more sensitive to microstructural differences and can be related to more specific micro-scale metrics (e.g., intra-axonal volume fraction) than diffusion tensor imaging (DTI), offering exceptional potential for clinical diagnosis and research into the white and gray matter. Currently DKI is acquired only at low spatial resolution (2–3 mm isotropic), because of the lower signal-to-noise ratio (SNR) and higher artifact level associated with the technically more demanding DKI. Higher spatial resolution of about 1 mm is required for the characterization of fine white matter pathways or cortical microstructure. We used restricted-field-of-view (rFoV) imaging in combination with advanced post-processing methods to enable unprecedented high-quality, high-resolution DKI (1.2 mm isotropic) on a clinical 3T scanner. Post-processing was advanced by developing a novel method for Retrospective Eddy current and Motion ArtifacT Correction in High-resolution, multi-shell diffusion data (REMATCH). Furthermore, we applied a powerful edge preserving denoising method, denoted as multi-shell orientation-position-adaptive smoothing (msPOAS). We demonstrated the feasibility of high-quality, high-resolution DKI and its potential for delineating highly myelinated fiber pathways in the motor cortex. REMATCH performs robustly even at the low SNR level of high-resolution DKI, where standard EC and motion correction failed (i.e., produced incorrectly aligned images) and thus biased the diffusion model fit. We showed that the combination of REMATCH and msPOAS increased the contrast between gray and white matter in mean kurtosis (MK) maps by about 35% and at the same time preserves the original distribution of MK values, whereas standard Gaussian smoothing strongly biases the distribution.