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JOM

, Volume 68, Issue 11, pp 2963–2972 | Cite as

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

  • Daniela M. UshizimaEmail author
  • Hrishikesh A. Bale
  • E. Wes Bethel
  • Peter Ercius
  • Brett A. Helms
  • Harinarayan Krishnan
  • Lea T. Grinberg
  • Maciej Haranczyk
  • Alastair A. Macdowell
  • Katarzyna Odziomek
  • Dilworth Y. Parkinson
  • Talita Perciano
  • Robert O. Ritchie
  • Chao Yang
Article

Abstract

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

Keywords

Mean Square Error Scanning Transmission Electron Microscopy Convolutional Neural Network Ceramic Matrix Composite CBIR System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work was supported by the Director, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences, of the US Department of Energy. Both the Early Career Research project and the Center for Applied Mathematics for Energy Related Applications (CAMERA) are under Contract No. DE-AC02- 05CH11231. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02- 05CH11231. We would like to thank Przemyslaw Oberbek, Materials Design Division, Faculty of Materials Science and Engineering, Warsaw University of Technology, Warsaw, Poland for preparing the SEM images. Also, the authors thank P. Nico and A. Wills for sharing samples of microCT of geological materials, and STEM of PMO, respectively. Additional thanks to B. Loring for supporting visualization schemes, and M. Alegro for participating on the development of multimodal registration methods.

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Copyright information

© The Minerals, Metals & Materials Society (outside the U.S.) 2016

Authors and Affiliations

  • Daniela M. Ushizima
    • 1
    • 7
    Email author
  • Hrishikesh A. Bale
    • 2
  • E. Wes Bethel
    • 1
  • Peter Ercius
    • 3
  • Brett A. Helms
    • 3
  • Harinarayan Krishnan
    • 1
  • Lea T. Grinberg
    • 4
  • Maciej Haranczyk
    • 1
  • Alastair A. Macdowell
    • 5
  • Katarzyna Odziomek
    • 6
  • Dilworth Y. Parkinson
    • 5
  • Talita Perciano
    • 1
  • Robert O. Ritchie
    • 2
    • 7
  • Chao Yang
    • 1
  1. 1.Computational Research DivisionLawrence Berkeley National LaboratoryBerkeleyUSA
  2. 2.Materials Sciences DivisionLawrence Berkeley National LaboratoryBerkeleyUSA
  3. 3.Molecular FoundryLawrence Berkeley National LaboratoryBerkeleyUSA
  4. 4.Memory and Aging CenterUniversity of California San FranciscoSan FranciscoUSA
  5. 5.Advanced Light Source DivisionLawrence Berkeley National LaboratoryBerkeleyUSA
  6. 6.Laboratory of Environmental Chemometrics, Faculty of ChemistryUniversity of GdanskGdańskPoland
  7. 7.University of California BerkeleyBerkeleyUSA

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