Synchrotron light sources are routinely used to perform imaging experiments. In this paper, we review the relevant computational stages, identify bottlenecks, and highlight future opportunities to streamline data acquisition for experimental microscopy workflows. We demonstrate our preliminary exploration with an end-to-end scientific workflow on Summit based on micro-computed tomography data. Computational elements include: 1) reconstruction of volumetric image data; 2) denoising with deep neural networks; and 3) non-local means based segmentation and quantitative analysis.

J.E. McClure, J.Yin, R.T. Armstrong, K.C. Maheshwari, S. WIlkinson, L. Vlcek, Y.D. Wang, M.A. Berrill, M. Rivers, “Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC“, J. Nichols et al. (Eds): SMC 2020, CCS 1315, pp 226-239, 2020.  abstract