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Invited lecture organized by RBI (CIR), Centre of Research Excellence for Data Science and TTP 2018 Project Proposal Initiatives

Ultra-fast X-ray tomographic imaging with applications in biology and materials science at the micrometer scale
Jun 5th 2018
Invited lecture organized by RBI (CIR), Centre of Research Excellence for Data Science and TTP 2018 Project Proposal Initiatives

First invited lecture of Centre of Research Excellence for Data Science and TTP 2018 Project Proposal Initiatives

June 18th 2018., 11:00 am

Ruđer Bošković Institute
Centre for Informatics and Computing
Blue lecture room

LECTURER
Dr. sc. Goran Lovrić
Centre d’Imagerie BioMédicale, EPFL,
Lausanne 1015, Switzerland

LECTURE

Ultra-fast X-ray tomographic imaging with applications in biology and materials science at the micrometer scale

Abstract 
Visualizing fast micrometer-scale dynamics in 3D is a key challenge for studies in functional biology, materials science, soft-condensed matter physics and many others. In the recent past synchrotron-based X-ray microtomography has proved as a valuable technique, providing high sensitivity to soft tissue by highly coherent X-rays combined with sufficient flux. As a result, we are now able to acquire full 4D tomographic datasets at 20 Hz and at spatial resolutions in the micrometer range coupled with continuous data streams of up to 8 GB/s, but the task still remains challenging as it requires the smooth interoperability of various aspects. In the present work we summarize out latest developments at the in the field of synchrotron-based X-ray imaging and give an overview on the imaging capabilities, methods and techniques in view of instrumentation, image acquisition and post-processing. As a prime example, we describe the world-wide first realization of in vivo lung tomography with pixel sizes down to about one micrometer for the study of microscopic lung physiology at the alveolar scale, by which we prove for the first time a microscopic heterogeneous distension pattern in lungs. Finally, we outline the current limitations and future strategies of the methodology in view of novel applications to related scientific fields. 

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