Voxel-based surface shape in multi-directional diffusion-weighted magnetic resonance imaging exhibits remarkable topological heterogeneity. Once the outline of an irregular shape is identified and segmented from a digital image, geometrical descriptors can be applied to numerical characterization the irregularity of the shapes surface. In our work the fractal and Euclidean dimensions of volume, area and mean radius for each surface were determined. These indices can be used as a surrogate parameter for determining the roughness of the surface. The relationship between indices from various voxels reveals the existence of distinct groups with significant structural differences which may be caused by underlying biological tissue types. This new method allows for the standardized continuous numerical classification of shape, which is useful for the quantitative analysis of altered surface morphology, e.g. biological tissue inflammatory diseases, aging, and development.


Разработка: студия Green Art