PET is one of the most sensitive clinical tools for early detections of small tumours, but its performance is dependent on multiple factors including image quality and human perception. Current methods relying on physical and numerical image quality phantoms are inadequate for evaluating clinical task-based performance, such as limits of lesion detection, due to lack of physiologic realism of the images.

In this work, we describe development and validation of the Lesion Synthesis Toolbox, an easy-to-use software to synthetize well-characterized, user-defined lesions in real patient PET data prior to image reconstruction and in corresponding CT images on GE Discovery line of PET/CT scanners.