Model-based image reconstruction for four-dimensional PET

摘要: Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers thoracic or upper abdominal region, the respiratory motion produces large distortions tumor shape size, affecting accuracy both treatment. Four-dimensional (4D) (gated) PET aims to reduce artifacts provide accurate measurement volume tracer concentration. A major issue 4D lack statistics. Since collected photons are divided into several frames scan, quality each reconstructed frame degrades as number increases. The increased noise heavily quantitative imaging. In this work, we propose method enhance performance by developing new technique reconstruction incorporation an organ model derived from 4D-CT images. based on well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During processes forward- backward-projection ML-EM iterations, all projection data acquired at different phases combined together update map aid deformable model, statistics therefore greatly improved. proposed algorithm was first evaluated computer simulations using mathematical dynamic phantom. Experiment moving physical phantom then carried out demonstrate increase signal-to-noise ratio over three-dimensional PET. Finally, applied patient case.