Study and comparison of different sensitivity models for a two-plane Compton camera

Abstract

Given the strong variations in the sensitivity of Compton cameras for the detection of events originating from different points in the field of view (FoV), sensitivity correction is often necessary in Compton image reconstruction. Several approaches for the calculation of the sensitivity matrix have been proposed in the literature. While most of these models are easily implemented and can be useful in many cases, they usually assume high angular coverage over the scattered photon, which is not the case for our prototype. In this work, we have derived an analytical model that allows us to calculate a detailed sensitivity matrix, which has been compared to other sensitivity models in the literature. Specifically, the proposed model describes the probability of measuring a useful event in a two-plane Compton camera, including the most relevant physical processes involved. The model has been used to obtain an expression for the system and sensitivity matrices for iterative image reconstruction. These matrices have been validated taking Monte Carlo simulations as a reference. In order to study the impact of the sensitivity, images reconstructed with our sensitivity model and with other models have been compared. Images have been reconstructed from several simulated sources, including point-like sources and extended distributions of activity, and also from experimental data measured with Na sources. Results show that our sensitivity model is the best suited for our prototype. Although other models in the literature perform successfully in many scenarios, they are not applicable in all the geometrical configurations of interest for our system. In general, our model allows to effectively recover the intensity of point-like sources at different positions in the FoV and to reconstruct regions of homogeneous activity with minimal variance. Moreover, it can be employed for all Compton camera configurations, including those with low angular coverage over the scatterer.

Performance evaluation of MACACO II Compton camera

“…The List Mode Maximum Likelihood Expectation Maximization (ML-EM) algorithm [14,15] was used for the reconstruction, and a maximum number of 10 iterations was chosen. For all images a Field-of-View (FOV) of 101 x 101 x 51 mm 3 has been used with a voxel size of 1 mm 3 .…”

Imaging of polychromatic sources through Compton spectral reconstruction

“…There are known effects that degrade the image and were not taken into account in the present work. One of them is the spatial resolution of the detectors, which is usually modeled using Gaussian probabilities around the measured position (Xu & He 2007, Muñoz et al 2018) and can lead to additional blurring if it is not corrected. Backscattered events also represent an important fraction of the measured data, especially for low energy photons.…”

Advanced Monte Carlo simulations of emission tomography imaging systems with GATE

“…The PRESTO toolkit (PET Reconstruction Software Toolkit) (Scheins and Herzog 2008, Scheins et al 2011, 2015 can also be used with GATE output, such as in Xu et al (2019). Finally, several Compton Camera reconstruction approaches have been used with GATE data, such as in Muñoz et al (2018), Kohlhase et al (2020) (MLEM or Origin Ensemble) or in Feng et al (2020), Maxim (2019) (with conical Radon transform modeling).…”