Analytic time-of-flight positron emission tomography reconstruction: three-dimensional case

Abstract

In a positron emission tomography (PET) scanner, the time-of-flight (TOF) information gives us rough event position along the line-of-response (LOR). Using the TOF information for PET image reconstruction is able to reduce image noise. The state-of-the-art TOF PET image reconstruction uses iterative algorithms. This study introduces an analytic TOF PET algorithm that focuses on three-dimensional (3D) reconstruction. The proposed algorithm is in the form of backprojection filtering, in which the backprojection is performed first by using a time-resolution profile function, and then a 3D filter is applied to the backprojected image. For the list-mode data, the backprojection is carried out in the event-by-event fashion, and the timing resolution determined weighting function is used along the projection LOR. Computer simulations are carried out to verify the feasibility of the proposed algorithm.

Poisson-noise weighted filter for time-of-flight positron emission tomography

“…Analytic image reconstruction methods for list-mode time-of-flight (TOF) positron emission tomography (PET) have been developed over the years [1][2][3][4]. One of the advantages of using TOF technology is its ability to reduce the image noise.…”

“…The filter can be two-dimensional (2D) or three-dimensional (3D). The filter developed in this study is specially targeted towards the backprojection filtering (BPF) algorithm used for TOF PET reconstruction [3,4]. In the BPF algorithm, each event is first backprojected into the image domain.…”

“…As pointed out in refs. [3,4], σ 2 and σ 1 are independent, and the user has freedom to choose σ 2 . The combined effect of σ 1 and σ 2 will be inverted by the tomographic filter, which depends on the sum of σ 1 + σ 2 .…”