Comparison of threshold-based and watershed-based segmentation for the truncation compensation of PET/MR images

Recently introduced combined PET/MR scanners need to handle the specific problem that a limited MR field of view sometimes truncates armor body contours, which prevents an accurate calculation of PET attenuation correction maps. Such maps of attenuation coefficients overbody structures are required for a quantitatively correct PET imagereconstruction. This paper addresses this problem by presenting a method that segments a preliminary reconstruction type of PET images,time of flight non-attenuation corrected (ToF-NAC) images, and outlining a processing pipeline that compensates the arm or body truncation with this segmentation. The impact of this truncation compensation is demonstrated together with a comparison of two segmentation methods, simple gray value threshold segmentation and a watershed algorithm on a gradient image. Our results indicate that with truncationcompensation a clinically tolerable quantitative SUV error is robustly achievable.