PET-CT enhancement by functional to anatomical image adaptation based on correlated nonlinear diffusion

Quantitative PET is essential for reliable and consistent diagnostics as well as for proper clinical image interpretation. It has been demonstrated that in co-registered dual-modalities, anatomical data can improve functional images by way of synergistic enhancement. We propose a practical method for PET-CT enhancement by functional to anatomical image adaptation based on 'correlated nonlinear diffusion'. In this method, functional image structures are adapted to corresponding anatomical images depending on morphology correlations. Testing the method on clinical data demonstrates image sharpening with significantly higher signal to noise ratio, while preserving the original appearance of the background. Systematic analysis of tumor lesions shows that improving quantification and delineation of functional information by using anatomical data becomes more significant with decreasing lesion size.