Structure-guided prior-driven implicit neural representations for time-of-flight PET image reconstruction.
OBJECTIVE Positron emission tomography (PET) reconstruction is an ill-posed inverse problem, particularly under low-count conditions where noise severely degrades image quality and quantitative accuracy. Although supervised learning approaches have demonstrated strong denoising capability, their performance often depen...