Monday 25th January |
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| 12:00 | Registration and lunch | |
| 13:30 | Opening | |
| 13:40 | László Szirmay-Kalos (Tech. Univ. Budapest, Hungary): Massively Parallel GPU-friendly Algorithms for PET |  |
| 14:30 | Andreas Alpers (Technische Universitaet Muenchen, Germany): Dynamic Discrete Tomography: Tractability vs. Intractability | |
| 15:00 | Coffee break | |
| 15:20 | Paolo Dulio (Politecnico di Milano, Italy): Applications of Uniqueness Results to Discrete Tomographic Reconstructions | In revision |
| 15:50 | Julianna Kostencka (Warsaw University of Technology, Poland): Correction of defocusing of object projections in optical diffraction tomography | |
| 16:20 | Piotr Makowski (Warsaw University of Technology, Poland): Limited angle Optical Diffraction Tomography with iterative image-domain masking | |
| 17:00 | Hungarian village dinner | |
Tuesday 26th January |
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| 9:30 | Suren A. Chilingaryan (Karlsruhe Institute of Technology, Germany): Performance-oriented instrumentation for high-speed synchrotron imaging | |
| 10:20 | Coffee break | |
| 10:40 | Lajos Rodek (EPAM, Hungary): Big Data: Size does matter! | |
| 11:30 | Kevin Mader (4Quant Ltd., Switzerland): Applying Big Data Solutions to Big Tomographic Problems |  |
| 12:00 | Lunch | |
| 13:30 | Willem Jan Palenstijn (CWI, Netherland): Distributing reconstruction algorithms using the ASTRA Toolbox | |
| 14:00 | Folkert Bleichrodt (CWI, Netherland): Rapid implementation of advanced tomography algorithms using the ASTRA toolbox with Spot operators | |
| 14:30 | Coffee break | |
| 14:50 | Gábor Szabó (University of Szeged, Hungary): Extreme Light Infrastructure (ELI) and big data | |
| 15:40 | Lajos Fülöp (ELI-ALPS, Hungary): The Integrated Control System and Scientific IT of ELI-ALPS | |
| 16:10 | Rajmund Mokso (Lund University, Sweden): Fast synchrotron phase tomography: perspectives for real-time data reduction and online quantification | |
| 19:00 | Fish Soup Dinner | |
Wednesday 27th January |
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| 9:30 | Ali Mohammad-Djafari (Laboratoire des Signaux & Systèmes , France): Hierarchical prior models for scalable Bayesian Tomography | |
| 10:20 | Coffee break | |
| 10:40 | Claudio Ferrero (ESFR, France): Generation, storage and analysis practices of computed tomography data at the ESRF: an overview | |
| 11:30 | Francesco Brun (Sincrotrone Trieste S.C.p.A, Italy): Enhanced and Flexible Software Tools for X-ray Computed Tomography at the Italian Synchrotron Radiation Facility Elettra | |
| 12:00 | Lunch | |
Applying Big Data Solutions to Big Tomographic Problems
With every more efficient detectors, higher flux, and stable beamlines, comes the ability to probe time and length-scales previously unachievable. Of particular interest are the massive scale projects like the Human Brain Project, adult Zebra fish imaging, and dynamic imaging. All involve thousands to millions of measurements at the highest possible resolutions to cover mm to m length scales. The task of processing and analyzing such large collections of measurements is exceptionally difficult. We show how the commodity hardware-based ‘Big Data’ solutions can be adapted to the scientific domain to address the processing terabytes worth of measurements in a parallel, distributed manner. Building on the distributed frameworks of Apache Spark and Spark Imaging Layer, we have extended the common tomographic and image processing tools to work on these images enabling the use of many machines in parallel and drastically accelerating the speed and ease with which these large datasets can be stitched and analyzed. Our most recent developments enable the data to be analyzed and processed in real-time using the latest streaming and micro-batch processing techniques. Unique such an approach allows for fault-tolerant, distributed analytics to process complicated datasets and eventually provide feedback to both experimentalists and their equipment to allow for adaptation of measurements.
