Maximum-likelihood estimation of emission and attenuation images in 3D PET from multiple energy window measurements

Abstract

This study explores the feasibility of incorporating energy information into a maximum-likelihood reconstruction of activity and attenuation (MLAA) framework. The attenuation and activity distributions were reconstructed from multiple energy window data, and a scatter function was added to the system model of the algorithm. The proposed energy-based method (MLAA-EB) was evaluated with simulated 3D phantom data, using the geometry and characteristics of a Siemens mMR PET-MR scanner. Results showed that the proposed algorithm is able to compensate for errors in the activity image caused by the incorrect assignment of attenuation values to the segmented MR. This is effective for small objects only, for large objects further solutions need to be found.

Joint Activity and Attenuation Reconstruction From Multiple Energy Window Data With Photopeak Scatter Re-Estimation in Non-TOF 3-D PET

“…Here we describe the main Energy-Based simultaneous Maximum Likelihood reconstruction of Activity and Attenuation with photopeak Scatter re-estimation (MLAA-EB-S), summarised in Algorithm 2. It can be seen as an evolution of MLAA-EB [30], improved on two main aspects: (i) the algorithm optimises one unique objective function, (ii) the activity and attenuation images are updated simultaneously. In particular, both unknown distributions λ and µ are reconstructed from all the available data: g UU , g UL and g LU .…”

“…To be able to handle high attenuating (or large) objects, a "four-step algorithm" was proposed alternating between various activity and attenuation image reconstruction steps. However, convergence of an alternating algorithm with each step optimising a different objective function can be problematic [30]. In addition, the evaluation of [29] used 2D phantoms and disregarded energy-measurement uncertainties.…”

“…We finally present results from simulated data and provide a comparison of the proposed method against MLAA from a single energy window acquisition. Similarly to previous published work [28]- [30], the current study is restricted to single scatter only.…”

Preliminary investigation of the impact of Axial Ring Splitting on Image Quality for the Cost Reduction of Total-Body PET

“…Thanks to STIR's, modular structure, all other features present in the library such as Time-of-Flight reconstruction [11], [12], regularised reconstruction [13]- [16], scatter [17], [18], motion correction [19], [20] and parametric imaging [21], resolution recovery [22] e.t.c., would be immediately available for Total Body PET scanners.…”

Corrección de eventos dispersos en algoritmos de reconstrucción tomográfica para PET

“…En este trabajo se aborda el análisis e implementación de algoritmos de modelado de eventos dispersos. Se desarrolla el algoritmo de modelado de eventos dispersos basado en Single Scatter Simulation (SSS) diseñado por Watson et al (1996), incorporando la segmentación por energía (Harrison et al, 1991) (Brusaferri at al, 2018). Este algoritmo es rápido, altamente paralelizable y es simple su incorporación a los algoritmos de reconstrucción (Bentourkia & Sarrhini, 2004) (Werling at al, 2000) Se añade el modelado de eventos dispersos a la reconstrucción de la imagen de emisión para realizar la corrección de los mismos (Cheng et al, 2007).…”