Subvoxel processing: a method for reducing partial volume blurring with application to in vivo MR images of trabecular bone.

Abstract

Partial volume blurring precludes accurate measurement of structural dimensions in the limited-resolution regime in which image voxel size is larger than the typical structural element to be resolved. Since acquiring images at increased resolution often exacts an unacceptable signal-to-noise ratio (SNR) penalty, methods to alleviate the adverse effects of partial volume blurring are instrumental for the accurate measurement of architectural parameters in applications such as predicting the mechanical competence of trabecular bone networks. In the current work, a novel post-processing method, referred to as "subvoxel processing," is described for increasing apparent image resolution. The method is applicable to volumes of interest containing material phases of two discrete signal intensities. The principal strategy consists of subdividing voxels and assigning voxel intensities to each subvoxel on the basis of local neighborhood criteria and strict mass conservation. In the current work, the method's accuracy has been evaluated using microcomputed tomography images (22 x 22 x 22 microm(3) voxel size) of human trabecular bone. The results demonstrate that subvoxel processing is significantly more accurate than trilinear interpolation in decreasing apparent voxel size, especially in the presence of noise. In addition, the method's effectiveness is illustrated with MR images of human trabecular bone acquired in vivo at 137 x 137 x 350 microm(3) voxel size. The subvoxel-processed images are shown to have architectural features characteristic of images acquired at higher spatial resolution.