Automated Least-Squares Calibration of the Coregistration Parameters for a Micro PET-CT System

PET-CT coregistration parameters can be derived from PET and CT images of a four-point-source calibration phantom for a micro PET-CT scanner. An automated segmentation method has been developed, based on thresholding and application of constraints on the sizes of point sources in the images. After point sources are identified on PET and CT images, coregistration is performed using an analytic rigid-body registration algorithm which is based on singular value decomposition and minimization of the coregistration error. The coregistration parameters thus derived can then be applied to coregister other PET and CT images from the same system. Twenty PET-CT images of the calibration phantom at various locations and/or orientations were obtained on a Siemens Inveon® Multi-Modality scanner. We tested the use of from 1 to 10 data sets to derive the coregistration parameters, and found that the coregistration accuracy improves with increasing number of data sets until it stabilizes. Coregistration of PET-CT images with an accuracy of
$0.33\pm 0.11~{\rm mm}$
has been achieved by this method on the Inveon Multi-Modality scanner.