3D segmentation of artery 18F-FDG PET/CT images in elderly utilizing affinity propagation

We present in this study a semi-automatic procedure to segment artery PET images in elderly subjects with atherosclerosis. The inflammation in the artery is a precursor of atheromatous plaque detachment and obstruction of blood vessels in the brain or the heart. CT images allow calcification detection in the arteries, and dynamic PET images with 18F-FDG allow to calculate glucose metabolism in the arteries to ultimately detect the inflammation. The goal of the artery image segmentation was to correlate the calcification on CT images to the artery metabolism on the PET images. First, all the artery images were delineated in each slice on the non-enhanced CT images with reference to anatomic atlases, and we used the active contours to locate the corresponding PET artery images at early time frames. All the artery images on PET were corrected for partial volume effect then each slice of the PET images was segmented with the algorithm of affinity propagation (AP). We introduced the segmentation of the dynamic histogram which is more accurate than segmenting image frames independently. The 3D reconstruction of the segmented arteries will be used in a future work to correlate glucose uptake to artery calcification.