1 / 12

Ultra-Fast Compton Camera Image Reconstruction

Explore cutting-edge advancements in Compton camera imaging technology for tumor radiation therapy and dose monitoring. Enhance image reconstruction through highly parallel data processing with innovative hardware and detector technologies. Learn about Geant4 simulations, prototype setups, and imaging workflows. Discover optimization strategies for reconstructing high-dimensional images efficiently. Plan for efficient migration to massive parallel programming for faster and more accurate image processing.

pdrew
Download Presentation

Ultra-Fast Compton Camera Image Reconstruction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 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

  2. 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

  3. 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

  4. 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

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

  6. 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’

  7. 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 

  8. 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

  9. 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?

  10. 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

More Related