High throughput software-based gradient tree boosting positioning for PET systems

Biomedical Physics & Engineering Express, vol. 7, pp. 055023

Abstract

Abstract The supervised machine learning technique Gradient Tree Boosting (GTB) has shown good accuracy for position estimation of gamma interaction in PET crystals for bench-top experiments while its computational requirements can easily be adjusted. Transitioning to preclinical and clinical applications requires near real-time processing in the scale of full PET systems. In this work, a high throughput GTB-based singles positioning C++ implementation is proposed and a series of optimizations are evaluated regarding their effect on the achievable processing throughput. Moreover, the crucial feature and parameter selection for GTB is investigated for the segmented detectors of the Hyperion IID PET insert with two main models and a range of GTB hyperparameters. The proposed framework achieves singles positioning throughputs of more than 9.5 GB/s for smaller models and of 240 MB/s for more complex models on a recent Intel Skylake server. Detailed throughput analysis reveals the key performance limiting factors, and an empirical throughput model is derived to guide the GTB model selection process and scanner design decisions. The throughput model allows for throughput estimations with a mean absolute error (MAE) of 175.78 MB/s.

Authors 7

1. Christian Wassermann corresponding Aachen High Performance Computing Group Computational Science and Engineering Division IT centre

   RWTH Aachen University

   Affiliation as printed

   High Performance Computing Group, Computational Science and Engineering Division, IT Center, RWTH Aachen University, 52074 Aachen, Germany

2. Florian Mueller corresponding Aachen Department of Physics of Molecular Imaging Systems Institute for Experimental Molecular Imaging

   RWTH Aachen University

   Affiliation as printed

   Department of Physics of Molecular Imaging Systems, Institute for Experimental Molecular Imaging, RWTH Aachen University, 52074 Aachen, Germany

3. Thomas Dey Aachen Department of Physics of Molecular Imaging Systems Institute for Experimental Molecular Imaging Faculty 05 Electrical Engineering and Information Technology

   RWTH Aachen University · FH Aachen

   Affiliation as printed

   Department of Physics of Molecular Imaging Systems, Institute for Experimental Molecular Imaging, RWTH Aachen University, 52074 Aachen, Germany

   Faculty 05 Electrical Engineering and Information Technology, FH Aachen University of Applied Sciences, 52074 Aachen, Germany

4. Janko Lambertus Aachen Department of Physics of Molecular Imaging Systems Institute for Experimental Molecular Imaging

   RWTH Aachen University

   Affiliation as printed

   Department of Physics of Molecular Imaging Systems, Institute for Experimental Molecular Imaging, RWTH Aachen University, 52074 Aachen, Germany

5. David Schug Aachen Department of Physics of Molecular Imaging Systems Institute for Experimental Molecular Imaging

   RWTH Aachen University

   Affiliation as printed

   Department of Physics of Molecular Imaging Systems, Institute for Experimental Molecular Imaging, RWTH Aachen University, 52074 Aachen, Germany

   Hyperion Hybrid Imaging Systems GmbH, 52074 Aachen, Germany

6. Volkmar Schulz Aachen Department of Physics of Molecular Imaging Systems Institute for Experimental Molecular Imaging Physics Institute III B

   Fraunhofer Institute for Digital Medicine · RWTH Aachen University

   Affiliation as printed

   Department of Physics of Molecular Imaging Systems, Institute for Experimental Molecular Imaging, RWTH Aachen University, 52074 Aachen, Germany

   Fraunhofer Institute for Digital Medicine MEVIS, 52074 Aachen, Germany

   Hyperion Hybrid Imaging Systems GmbH, 52074 Aachen, Germany

   Physics Institute III B, RWTH Aachen University, 52074 Aachen, Germany

7. Julian Miller Aachen High Performance Computing Group Computational Science and Engineering Division IT centre

   RWTH Aachen University

   Affiliation as printed

   High Performance Computing Group, Computational Science and Engineering Division, IT Center, RWTH Aachen University, 52074 Aachen, Germany