Algorithm-driven Advances for Scientific CT Instruments: From Model-based to Deep Learning-based Approaches

Venkatakrishnan, S. V.; Mohan, K. Aditya; Ziabari, Amir Koushyar; Bouman, Charles A.

doi:10.48550/arxiv.2104.08228

Cited by 1 publication

(2 citation statements)

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“…Many machine learning (ML) techniques have been successfully used and integrated to light source and electron microscopy data analysis workflows to enhance and improve the quality of images and reconstructions [9,36,56], including image denoising [62,39], artifact reduction [65] and feature extraction [51]. These techniques can also be used for accelerating the performance of workflows and data acquisition [38].…”

Section: Related Workmentioning

confidence: 99%

“…The ptychographic reconstruction process is typically data-intensive, requiring hundreds of iterations over diffraction patterns and the reconstructed object. Moreover, if the goal is to recover a 3D volumetric image, then tomographic (or laminographic) reconstruction techniques need to be performed after ptychographic reconstruction [30,56], further increasing the computational demand and execution time of the processing pipeline [10,43].…”

Section: Introductionmentioning

confidence: 99%

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High-Performance Ptychographic Reconstruction with Federated Facilities

Biçer¹,

Yu²,

Ching³

et al. 2021

Preprint

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Beamlines at synchrotron light source facilities are powerful scientific instruments used to image samples and observe phenomena at high spatial and temporal resolutions. Typically, these facilities are equipped only with modest compute resources for the analysis of generated experimental datasets. However, high data rate experiments can easily generate data in volumes that take days (or even weeks) to process on those local resources. To address this challenge, we present a system that unifies leadership computing and experimental facilities by enabling the automated establishment of data analysis pipelines that extend from edge data acquisition systems at synchrotron beamlines to remote computing facilities; under the covers, our system uses Globus Auth authentication to minimize user interaction, funcX to run user-defined functions on supercomputers, and Globus Flows to define and execute workflows. We describe the application of this system to ptychography, an ultrahigh-resolution coherent diffraction imaging technique that can produce 100s of gigabytes to terabytes in a single experiment. When deployed on the DGX A100 ThetaGPU cluster at the Argonne Leadership Computing Facility and a microscopy beamline at the Advanced Photon Source, our system performs analysis as an experiment progresses to provide timely feedback.

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