Approximation of optimal surface parameterizations and the application in cerebral cortex mapping.

Optimal parameterizations of surface meshes are useful in the mapping and visualization of the cerebral cortex, the outer layer of the human brain. We propose two new methods to compute approximations of the optimal parameterizations, and apply these methods to human cortical surface meshes extracted from magnetic resonance images. Our methods approximate the parameterizations in a low-dimensional subspace spanned by the coordinate vectors of an initial parameterization and the low-frequency eigenvectors of a mesh Laplacian. This low-dimensional approximation reduces the computational complexity while minimizing the error.

Statistical ray method for deriving reflection models of rough surfaces.

A statistical ray method is developed for deriving reflection models of rough surfaces. Using this method, we derive generic equations of reflection due to single scattering. We have studied an isotropic surface with Gaussian statistics, and the derived bidirectional reflectance distribution function is found with four distinct regimes, namely, mirror reflection, grazing reflection, retroreflection, and normal reflection. An explicit form of self-shadowing for a surface with Gaussian statistics is also derived, and the result agrees well with computer simulation. Our solution is useful to describe the entire reflection of a highly or moderately smooth surface and offers a basis for studying multiple scattering. While focusing on optical reflection, the approach also applies to other waves if the assumptions are satisfied.

Statistical analysis of morphological differences between brains.

Recent study in neuroscience has observed evidence that the anatomic structures in human brains might have certain connection with the functioning. This triggers the interest in morphological study of cortical surfaces and in comparison of different ethnic groups. This article compares the MRI brain datasets of 10 Chinese and 10 Caucasians. A statistical analysis was applied to the white matter volumes in these datasets and evaluate the dissimilarities between the two groups using various intuitive measures. This analysis has revealed systematic morphological differences between the two ethnic groups.

Intravenous polyethylene glycol inhibits the loss of cerebral cells after brain injury.

We have tested the effectiveness of polyethylene glycol (PEG) to restore the integrity of neuronal membranes after mechanical damage secondary to severe traumatic brain injury (TBI) produced by a standardized head injury model in rats. We provide additional detail on the standardization of this model, particularly the use and storage of foam bedding that serves to both support the animal during the impact procedure-and as a dampener to the acceleration of the brass weight. Further, we employed a dye exclusion technique using ethidium bromide (EB; quantitative evaluation) and horseradish peroxidase (HRP; qualitative evaluation). Both have been successfully used previously to evaluate neural injury in the spinal cord since they enter cells when their plasma membranes are damaged. We quantified EB labeling (90 microM in 110 microL of sterile saline) after injection into the left lateral ventricle of the rat brain 2 h after injury. At six h after injection and 8 h after injury, the animals were sacrificed and the brains were analyzed. In the injured rat brain, EB entered cells lining and medial to the ventricles, particularly the axons of the corpus callosum. There was minimal EB labeling in uninjured control brains, limited to cells lining the luminal surfaces of the ventricles. Intravenous injections of PEG (1 cc of saline, 30% by volume, 2000 MW) immediately after severe TBI resulted in significantly decreased EB uptake compared with injured control animals. A similar result was achieved using the larger marker, HRP. PEG-treated brains closely resembled those of uninjured animals.

Adaptive image-processing technique and effective visualization of confocal microscopy images.

A common observation about confocal microscopy images is that lower image stacks have lower voxel intensities and are usually blurred in comparison with the upper ones. The key reasons are light absorption and scattering by the objects and particles in the volume through which light passes. This report proposes a new technique to reduce such noise impacts in terms of an adaptive intensity compensation and structural sharpening algorithm. With these image-processing procedures, effective 3D rendering techniques can be applied to faithfully visualize confocal microscopy data.