X-ray scattering by the fused silica surface etched by low-energy Ar ions.

Anomalously high x-ray scattering at a wavelength of 0.154 nm by super-polished substrates of fused silica, which were etched by the argon ions with the energy of 300 eV, is detected. The scattering intensity increases monotonically with increasing of the etching depth. The effect is explained by the scattering on the volume inhomogeneities with the lateral size greater than 0.5 µm of the subsurface "damaged" layer. The concentration of volume inhomogeneities increases with the increase of the fluence of argon ions, but the concentration of implanted argon atoms in the layer quickly reaches the maximum value and then begins a trend of going down. The thickness of the "damaged" layer is approximately equal to the penetration depth of the Ar atoms and can be directly determined from the x-ray specular reflection. It is shown that the presence of volume inhomogeneities of the subsurface "damaged" layer does not affect the geometric roughness of the surface. The observed effect imposes limitations on the usage of grazing incidence x-ray optics without reflective coatings and of the diffuse x-ray scattering (DXRS) method for studying the substrate roughness. A new method that potentially enables to evaluate the applicability of the DXRS method in practice is proposed.

Fluid registration of diffusion tensor images using information theory.

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.