SES-05: Deep Learning-based Inspection

• Single-Shot X-ray to Multi-View Projections for 3D Pork Shoulder Bone Analysis

Michiel Pieters¹, Pieter Verboven¹, Bart Nicolaï^1,2

¹Ku Leuven, Belgium; ²Flanders Centre of Postharvest Technology,Belgium

• Superimposing Synthetic Defects into Real CT Scans for Advanced Probability of Detection Evaluation

Miroslav Yosifov^1,2, Bernhard Fröhler¹, Jan De Beenhouwer², Jan Sijbers², Johann Kastner¹, Christoph Heinzl^3,4

¹University of Applied Sciences Upper Austria, Wels, Austria; ²imec-Vision Lab, Dept. of Physics, University of Antwerp, Universiteitsplein 1, 2610 Antwerpen, Belgium; ³University of Passau, Innstraße 43, Passau, Germany; ⁴Fraunhofer Institute for Integrated Circuits IIS, Division Development Center X-ray Technology, Flugplatzstraße 75, Fürth, Germany

• Combining Deep Learning and scatterControl for High-Throughput X-ray CT based Non-Destructive Characterization of Large-Scale Casted Metallic Components

Amir Koushyar Ziabari¹, Mohamed Hakim Bedhief², Obaidullah Rahman¹, Singanallur Venkatakrishnan¹, Paul Brackman³, Peter Katuch²

¹Oak Ridge National Lab, United States of America; ²Carl ZEISS IMT GmbH; ³ZEISS Industrial Quality Solutions

• Proximal Neural Networks based reconstruction for few-view CT applications

Hoang Trieu Vy LE¹, C. Bossuyt², J. Escoda¹, M. Costin¹, J. De Beenhouwer², J. Sijbers²

¹CEA, France; ²IMEC - Vision Lab, University of Antwerp, 2610 Antwerpen, Belgium