Comparing reconstruction algorithms using a multi-variate analysis

We propose a voxel-based multi-variate analysis to evaluate the performance of tomographic image reconstruction. This technique allows simultaneous comparison of the underlying task with resolution and noise behavior as well as other effects across the entire volume for different reconstructions. We demonstrate the idea with a 2D simulation and apply the method to compare 3D [¹⁵O]water studies reconstructed by 3D reprojection (3DRP) and Fourier rebinning (FORE) for a motor task. The difference between the two reconstructions was found to be significant relative to the baseline-activation effect (26% vs. 74% for single-session analysis and 32% vs. 68% for 4-session analysis). Although the differences in resolution and noise characteristics are similar to those reported in the literature, the major pattern that separates the two reconstructions is a mean difference in the axial direction. However, both 3DRP and FORE are capable of discriminating the baseline scans from the activation scans