Automated PET/CT Cardiac Registration for Accurate Attenuation Correction

Alignment of PET and CT images is essential for accurate measurements of cardiac perfusion. Misalignment can produce an erroneous attenuation map that projects lung attenuation parameters onto the heart wall, thereby underestimating the attenuation, and creating artifactual areas of hypoperfusion which may be misinterpreted as myocardial ischemia or infarction. The main cause of misregistration between CT and PET images is the respiratory motion of the patient. In this paper, an automated cardiac software alignment method is proposed to overcome this motion artifact. In this approach, the heart is extracted from the PET data through windowing and c-mean clustering, and the CT scans are segmented to obtain the corresponding heart geometry. From this processed data, the heart geometries are registered, and a motion correction vector is calculated such that the alignment error of the two modalities is minimized. Results of this optimization procedure have been evaluated on 24 patient PET/CT cardiac data sets producing accurate cardiac alignment which eliminated PET/CT misregistration attenuation correction artifact