Fastest Data Processing in Image Reconstruction for Compton Camera Imaging

2. 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

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

4. 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

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

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

7. 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 Aof device 2nd Optimize image x’

8. Objectives within the project – CCI Image Reconstruction 1st Construct model Aof 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 

9. 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

10. 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?

11. 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