Development and evaluation of an in-beam PET system for proton therapy monitoring.

Objective: In-beam positron emission tomography (PET) has important development prospects in real-time monitoring of proton therapy. However, in the beam-on operation, the high bursts of radiation events pose challenges to the performance of the PET system.

Approach: In this study, we developed a dual-head in-beam PET system for proton therapy monitoring and evaluated its performance.

Deep denoiser prior driven relaxed iterated Tikhonov method for low-count PET image restoration.

. Low-count positron emission tomography (PET) imaging is an efficient way to promote more widespread use of PET because of its short scan time and low injected activity. However, this often leads to low-quality PET images with clinical image reconstruction, due to high noise and blurring effects.

Proton spot dose estimation based on positron activity distributions with neural network.

Background: Positron emission tomography (PET) has been investigated for its ability to reconstruct proton-induced positron activity distributions in proton therapy. This technique holds potential for range verification in clinical practice. Recently, deep learning-based dose estimation from positron activity distributions shows promise for in vivo proton dose monitoring and guided proton therapy.

In-beam PET monitoring of proton therapy: a method for filtering prompt radiation events.

. In-beam positron emission tomography (PET) is a promising technology for real-time monitoring of proton therapy. Random coincidences between prompt radiation events and positron annihilation photon pairs can deteriorate imaging quality during beam-on operation.