New technologies for x-ray microscopy: phase correction and fully automated deep learning based tomographic reconstruction

Matthew Andrew; Lars Omlor; Andriy Andreyev; Ravikumar Sanapala; Mohsen Samadi Khoshkhoo

doi:10.1117/12.2596592

9 September 2021 New technologies for x-ray microscopy: phase correction and fully automated deep learning based tomographic reconstruction

Matthew Andrew, Lars Omlor, Andriy Andreyev, Ravikumar Sanapala, Mohsen Samadi Khoshkhoo

Author Affiliations +

Proceedings Volume 11840, Developments in X-Ray Tomography XIII; 118400I (2021) https://doi.org/10.1117/12.2596592
Event: SPIE Optical Engineering + Applications, 2021, San Diego, California, United States

Abstract

The progress of scientific research and technology development greatly depends upon effective imaging solutions for characterizing the properties and behaviors of materials. Revealing details of microstructure, ideally in 3D, is a critical part of this understanding, whether the goal is to develop and confirm models that describe material properties and behaviors or simply to visualize structural details. ZEISS offers 3D X-ray microscopes (XRM): advanced imaging solutions that have removed major hurdles for three-dimensional imaging by achieving high contrast and submicron resolution imaging even for relatively large samples. These groundbreaking advances in non-destructive, three-dimensional (3D) imaging empower a broad range of technical disciplines.

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Matthew Andrew, Lars Omlor, Andriy Andreyev, Ravikumar Sanapala, and Mohsen Samadi Khoshkhoo "New technologies for x-ray microscopy: phase correction and fully automated deep learning based tomographic reconstruction", Proc. SPIE 11840, Developments in X-Ray Tomography XIII, 118400I (9 September 2021); https://doi.org/10.1117/12.2596592

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