2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDSS-CIMM.5
Paper Title Strategies of Deep Learning for Tomographic Reconstruction
Authors Xiaogang Yang, Christian Schroer, Deutsches Elektronen-Synchrotron DESY, Germany
SessionSS-CIMM: Special Session: Computational Imaging for Materials and Microscopy
LocationArea B
Session Time:Monday, 20 September, 13:30 - 15:00
Presentation Time:Monday, 20 September, 13:30 - 15:00
Presentation Poster
Topic Special Sessions: Computational Imaging for Materials and Microscopy
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract In this article, we introduce three different strategies of tomographic reconstruction based on deep learning. These algorithms are model-based learning for iterative optimization. We discuss the basic principles of developing these algorithms. The performance of them is analyzed and evaluated both on theory and simulation reconstruction. We developed open-source software to run these algorithms in the same framework. From the simulation results, all these deep learning algorithms showed improvements in reconstruction quality and accuracy where the strategy based on Generative Adversarial Networks showed the advantage especially.