With the advance in PET technology and especially scintillating detectors, spatial resolution in the order of 2 mm FWHM are becoming a reality, allowing a more in-depth exploration of complex organs such as the human brain. Subject movement during imaging has always been a factor contributing to image degradation, but is becoming a major limitation in the achievement of the full spatial resolution potential of modern scanners. We propose to demonstrate that the geometric transfer matrix (GTM) method which is a popular method used for partial volume correction (PVC) can be further extended to head movement correction (HMC) when it is associated with some means of head motion tracking (HMT), and is thereafter referred to as the GTM-HMC method. Computer simulations of arbitrary movements were carried out on in a single magnetic resonance image (MRI) volume that was segmented into various functional regions. Data were analyzed without any correction, after application of the GTM-PVC method alone, and after application of the new GTM-HMC method. Results indicate an excellent recovery capability of the new algorithm in the presence of small movements, with typical root-mean square error of less than 1% over the course of a 90-min study. In the presence of noise, the algorithm did not suffer from increased variance compared to when performing GTM-PVC alone. This method is expected to be of great interest since it can account for all detected movements, does not require the reconstruction of intermediate images with inferior statistics, nor is as computerintensive as event-driven movement correction methods.