Tuning and Comparing Spatial Normalization Methods

A direct voxel tracking method for four-dimensional Monte Carlo dose calculations in deforming anatomy

In this work we present a method of calculating dose in deforming anatomy where the position and shape of each dose voxel is tracked as the anatomy changes. The EGSnrc/DOSXYZnrc Monte Carlo code was modified to calculate dose in voxels that are deformed according to deformation vectors obtained from a nonlinear image registration algorithm. The defDOSXYZ code was validated by consistency checks and by comparing calculations against DOSXYZnrc calculations. Calculations in deforming phantoms were compared with a dose remapping method employing trilinear interpolation. Dose calculations with the deforming voxels agree with DOSXYZnrc calculations within 1%. In simple deforming rectangular phantoms the trilinear dose remapping method was found to underestimate the dose by up to 29% for a 1.0 cm voxel size within the field, with larger discrepancies in regions of steep dose gradients. The agreement between the two calculation methods improved with smaller voxel size and deformation magnitude. A comparison of dose remapping from Inhale to Exhale in an anatomical breathing phantom demonstrated that dose deformations are underestimated by up to 16% in the penumbra and 8% near the surface with trilinear interpolation.

The creation of a brain atlas for image guided neurosurgery using serial histological data

Digital and print brain atlases have been used with success to help in the planning of neurosurgical interventions. In this paper, a technique presented for the creation of a brain atlas of the basal ganglia and the thalamus derived from serial histological data. Photographs of coronal histological sections were digitized and anatomical structures were manually segmented. A slice-to-slice nonlinear registration technique was used to correct for spatial distortions introduced into the histological data set at the time of acquisition. Since the histological data were acquired without any anatomical reference (e.g., block-face imaging, post-mortem MRI), this registration technique was optimized to use an error metric which calculates a nonlinear transformation minimizing the mean distance between the segmented contours between adjacent pairs of slices in the data set. A voxel-by-voxel intensity correction field was also estimated for each slice to correct for lighting and staining inhomogeneity. The reconstructed three-dimensional (3D) histological volume can be viewed in transverse and sagittal directions in addition to the original coronal. Nonlinear transformations used to correct for spatial distortions of the histological data were applied to the segmented structure contours. These contours were then tessellated to create three-dimensional geometric objects representing the different anatomic regions in register with the histological volumes. This yields two alternate representations (one histological and one geometric) of the atlas. To register the atlas to a standard reference MR volume created from the average of 27 T1-weighted MR volumes, a pseudo-MRI was created by setting the intensity of each anatomical region defined in the geometric atlas to match the intensity of the corresponding region of the reference MR volume. This allowed the estimation of a 3D nonlinear transformation using a correlation based registration scheme to fit the atlas to the reference MRI. The result of this procedure is a contiguous 3D histological volume, a set of 3D objects defining the basal ganglia and thalamus, both of which are registered to a standard MRI data set, for use for neurosurgical planning.