KIT – University of the State of Baden-Württemberg and National Laboratory of the Helmholtz Association www.kit.edu Institute for Data Processing and Electronics.

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Presentation transcript:

KIT – University of the State of Baden-Württemberg and National Laboratory of the Helmholtz Association Institute for Data Processing and Electronics Introducing Xiaoli Yang “Optimization of Algebraic Reconstruction Methods on Parallel Computing Architecture”

22 Who am I ? Bachelor 2004 – 2008 Electronic Science and Technology Master 2008 – 2011 Electronics Engineering Career 2011, 3m Software- Programming PhD 2011 – 2015 Electronics Engineering (CSC) Xiaoli Yang My education

33 Professional Interests Research Computer tomography Low-dose X-ray CT reconstruction Optimization mehtods Image quality assessment Parallel computing technique Technologies Algebraic reconstruction technique (ART) Compressive sampling (CS) theory Regularizations: total variation (TV), wavelet transform, … Parameter determination: L-curve Hadoop cluster for parallel computing

44 Reconstruction algorithms/solvers Project: X-ray CT reconstruction at ANKA Parameter determination min ||Ax-b|| 2 + λ ||x|| TV Solver: conjugate gradient L-curve Paper (to be published) Few-view reconstruction of beetle and frog embryo Parallel computing and automatic implementation Parallel beam: 2D  3D Hadoop cluster Automatic implementation

55 The Future What is missing? Advanced solvers - fast convergence - Optimized for task Regularizations - TV, wavelet, … - Affects on reconstruction? Real 3D reconstruction - Large system matrix - intensive computing Forward model - Imaging geometry - motion blurring of fast tomography Applications - ANKA X-ray tomography - Electron microscopy tomography - Others …

66 The Future What is missing? Motion blurring correction for fast tomography Application in On which new technologies or research trends we need to keep an eye on?

77 Project Optimization of the algebraic tomographic reconstruction Reconstruction on the parallel computing architecture Data Source: ANKA (sparsely sampling ) Data Source: ANKA (sparsely sampling ) Reconstruction Optimization Parallel Computing Algorithm development Computing structure with Hadoop TVAL 3 TwIST CGTV Manual Parallelization Automatic Implementation

88 The Future What is missing? Advanced solvers - fast convergence - Optimized for task Regularizations - TV, wavelet, … - Affect on reconstruction? Real 3D reconstruction - Large system matrix - intensive computing Forward model - Imaging geometry - motion blurring of fast tomography Resolution improvements - Multi-scale resolution - Multi-grid method Applications - ANKA X-ray tomography - Electron microscopy tomography - Others …