Fastest Data Processing in Image Reconstruction for Compton Camera Imaging DTSP-Workshop on “Ultra-fast data transfer and reconstruction” (pillar 2)  Burg Obbendorf, Jülich  May 9th - May 10th Sebastian Schöne, Radiation Physics, HZDR

About us – HZDR – Helmholtz-Zentrum Dresden-Rossendorf Helmholtz-Institut Freiberg HZDR Research Site Leipzig The Rossendorf Beamline at ESRF, Grenoble, France maps.google.de

About us – HZDR – Helmholtz-Zentrum Dresden-Rossendorf Joined the Helmholtz association in 2011 More than 800 employees Research in the sectors health, energy, and matter Research facilities Superconducting electron accelerator ELBE as a source of high brilliance and low emittance for the production of Bremsstrahlung, neutrons, infrared FEL-radiation High Magnetic Field Laboratory HLD to generate highest pulsed magnetic fields Ion Beam Center for Materials Research … Involved in international experiments at the ESRF, GSI, FAIR Medical research PET center in radiopharmacy, therapy and medical imaging OncoRay – National Center for Radiation Research in Oncology DKTK

Cross cutting activities Objectives within the project – CCI Image Reconstruction Ultrafast data transfer and reconstruction Intelligent programmable hardware Near detector optical signal transmission Fastest data processing with highly parallel architectures Technologies for assembling highly integrated detectors 3D ASICs Mixed-signal ASICs 3D / high-Z sensors Packaging and interconnection technologies Innovative detector structure materials Detector types Fast photon and X-ray detectors Diamond detectors Detectors for thermal neutrons Compact gas detectors Cross cutting activities

Why Compton camera imaging (CCI) ? Objectives within the project – CCI Image Reconstruction Why Compton camera imaging (CCI) ? Tumor radiation therapy Protons (and light ions) More local dose deposition w.r.t. photon irradiation Dose monitoring Prompt gammas SPECT By means of Compton cameras A. Müller, Geant4 simulations

Principle of Compton camera imaging Objectives within the project – CCI Image Reconstruction Principle of Compton camera imaging Q, Eg P, L1 R, L2 q scatter P absorber g Scatter Absorber apex axis R

Objectives within the project – CCI Image Reconstruction Our prototypes C. Golnik, CZT-CZT-Setup T. Kormoll, CZT-LSO-Setup

Objectives within the project – CCI Image Reconstruction Imaging workflow Study object x Measurement y = A(x) Measurement series y Reconstruction x’ = A-1(y) Reconstructed image x’ ≈ x 1st Construct model A of device 2nd Optimize image x’

1st Construct model A of device Objectives within the project – CCI Image Reconstruction 1st Construct model A of device + y=A(x) high dimensional: y \in R8, x \in R4 Measured data handled as distributions Additional influences Cross sections Camera geometry …. Medium memory consuming High time consumption ~1 s/event/core Assumption: 10k events/s Assumption: 100k filtered events per recording 

Objectives within the project – CCI Image Reconstruction 2nd Optimize image x’ 22Na point @ (0,4,7) cm Eventfilter 1275 keV +/- 20% Standard algorithms exist Less complex Less time consuming High memory consumption e.g. operate on n*10G floats Summed backprojection 1,2,…,7,50,100,500,800 events MLEM, Iteration 1, 2 … 25 800 events

Status quo Plans Wishes Objectives within the project – CCI Image Reconstruction Status quo Plans Wishes Python NumPy + SciPy Workstation & HPC cluster Migration to massive parallel programming Selective (module) Successive Permanent Parallel drop-in replacement ? (beam time, treatment room) Interface to high-level programming Python integration OpenCL vs. CUDA Multi-GPGPU GPGPU-alternatives …. Are ‘general purpose’ implementations reasonable?

HPC @ HZDR HPC @ TU Dresden Objectives within the project – CCI Image Reconstruction HPC @ HZDR HPC @ TU Dresden 2 HPC clusters Small GPGPU cluster S1070 C2070 Multiple HPC cluster GPGPU cluster S1070 S2050 C2070 … Lectures on massive parallel programming CUDA Research Center Awarded CUDA Center of Excellence