TY - JOUR T1 - Motion detection from raw list-mode HRRT data and improved frame-by-frame realignment for motion correction JF - Journal of Nuclear Medicine JO - J Nucl Med SP - 589 LP - 589 VL - 50 IS - supplement 2 AU - Shailendra Segobin AU - Julian Matthews AU - David Coope AU - Steve Williams AU - Matthew Jones AU - Rainer Hinz AU - Karl Herholz Y1 - 2009/05/01 UR - http://jnm.snmjournals.org/content/50/supplement_2/589.abstract N2 - 589 Objectives Head movement is a problem in PET studies, especially at high spatial resolution. Frame-by-frame (FBF) realignment can be used to correct motion between frames but is unable to correct for motion during frames. A novel method for motion correction is presented, using a centroid technique to detect and subsequently reframe data so as to minimise within frame movement and enable more accurate frame-by-frame realignment. Methods Motion is detected by calculating the radioactivity centroid within planograms of opposing heads directly from the listmode data and sampled every second. High frequency changes in these curves atypical of tracer redistribution result from subject motion, enabling reframing into relatively motionless frames. Reconstructions without attenuation and scatter correction are then used to estimate motion parameters by registration to an attenuation map reconstructed from a transmission scan. These parameters are then used to realign and forward project the attenuation maps into sinograms, enabling accurate attenuation and scatter correction. The data is then reconstructed with these corrections and finally realigned to each other. The method was compared to conventional FBF realignment. Results On 4 FDG-PET scans recorded on a High Resolution Research Tomograph (HRRT, FWHM 2.5mm), anatomical definition of small regions (e.g. colliculi) was visually improved. Time-Activity Curves (TACs) of selected regions of the brain showed improved motion correction in the early short frames and where the centroid demonstrated evidence of movements within later frames. Conclusions This method corrects for motion without use of external equipment and reduces variability of kinetic activity measurements ER -