MRI-PET Registration with Automated Algorithm

TLDR

Prior work has demonstrated an automated method for aligning PET images within the same modality. This study extends that method to enable cross‑modality registration of MRI and PET brain images from a single subject. The algorithm aligns the images by minimizing the standard deviation of PET pixel values corresponding to each MRI pixel, without requiring fiducial markers or manual structure identification, after removing non‑brain regions from the MR image. Validation on patients with rigidly fixed stereotaxic fiducials showed mean 3‑D errors below 2 mm and maximum errors below 3 mm, with computation times of 3–9 min for FDG PET and 20–30 min for noisy H215O PET.

Abstract

Objective We have previously reported an automated method for within-modality (e.g., PET-to-PET) image alignment. We now describe modifications to this method that allow for cross-modality registration of MRI and PET brain images obtained from a single subject. Methods This method does not require fiducial markers and the user is not required to identify common structures on the two image sets. To align the images, the algorithm seeks to minimize the standard deviation of the PET pixel values that correspond to each MRI pixel value. The MR images must be edited to exclude nonbrain regions prior to using the algorithm. Results and Conclusion The method has been validated quantitatively using data from patients with stereotaxic fiducial markers rigidly fixed in the skull. Maximal three-dimensional errors of <3 mm and mean three-dimensional errors of <2 mm were measured. Computation time on a SPARCstation IPX varies from 3 to 9 min to align MR image sets with [18F]fluorodeoxyglucose PET images. The MR alignment with noisy H215O PET images typically requires 20–30 min.