Achieving  fast high-resolution 3D imaging by combining synchrotron x-ray microCT, advanced algorithms, and high performance data management

Dilworth Y. Parkinson; Joseph I. Pacold; Miela Gross; Tristan D. McDougall; Chandler Jones; John Bows; Ian Hamilton; Danil E. Smiles; Stefano De Santis; Alessandro Ratti; Daniël E. Pelt; James Sethian; Harold Barnard; Joshua Peterson; Alvaro Ramirez-Hong; Alastair MacDowell; David K. Shuh

doi:10.1117/12.2307272

8 June 2018 Achieving fast high-resolution 3D imaging by combining synchrotron x-ray microCT, advanced algorithms, and high performance data management

Dilworth Y. Parkinson, Joseph I. Pacold, Miela Gross, Tristan D. McDougall, Chandler Jones, John Bows, Ian Hamilton, Danil E. Smiles, Stefano De Santis, Alessandro Ratti, Daniël E. Pelt, James Sethian, Harold Barnard, Joshua Peterson, Alvaro Ramirez-Hong, Alastair MacDowell, David K. Shuh

Author Affiliations +

Proceedings Volume 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V; 106560S (2018) https://doi.org/10.1117/12.2307272
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

Synchrotrons like the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory (LBNL) are an extremely bright source of X-rays. In recent years, this brightness has been coupled to large increases in detector speeds (including CMOS and sCMOS detectors) to enable microCT 3D imaging at unprecedented speeds and resolutions. The micro-CT Beamline at the ALS has been used by geologists simulating volcanic eruptions, engineers developing hierarchical materials that are tough at high temperature, and biologists studying water transport in plants experiencing drought stress. In each case, 3D processes occurring over seconds to minutes are studied with micrometer resolution-and in each case, advanced algorithms and data management have been critical in completing successful experiments. This article will describe the collaboration of the ALS with the National Energy Research Scientific Computing Center (NERSC) supercomputer to develop a super-facility, combining powerful X-rays with enormous computing power and describe the collaboration of the ALS with the Center for Applied Mathematics for Energy Research Applications (CAMERA) at LBNL to develop algorithms that can not only handle the enormous data sizes now being collected, but do so fast enough to give scientists feedback during their experiments in real-time. A major focus of CAMERA has been to apply new machine learning approaches to tomography, to improve image reconstruction, automate feature detection, and allow image search.

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Dilworth Y. Parkinson, Joseph I. Pacold, Miela Gross, Tristan D. McDougall, Chandler Jones, John Bows, Ian Hamilton, Danil E. Smiles, Stefano De Santis, Alessandro Ratti, Daniël E. Pelt, James Sethian, Harold Barnard, Joshua Peterson, Alvaro Ramirez-Hong, Alastair MacDowell, and David K. Shuh "Achieving fast high-resolution 3D imaging by combining synchrotron x-ray microCT, advanced algorithms, and high performance data management", Proc. SPIE 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V, 106560S (8 June 2018); https://doi.org/10.1117/12.2307272

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