LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction

Johannes Leuschner; Maximilian Schmidt; Daniel Otero Baguer; Peter Maass

doi:10.1038/s41597-021-00893-z

Scientific Data (Apr 2021)

LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction

Johannes Leuschner,
Maximilian Schmidt,
Daniel Otero Baguer,
Peter Maass

Affiliations

Johannes Leuschner: Center for Industrial Mathematics, University of Bremen
Maximilian Schmidt: Center for Industrial Mathematics, University of Bremen
Daniel Otero Baguer: Center for Industrial Mathematics, University of Bremen
Peter Maass: Center for Industrial Mathematics, University of Bremen

DOI: https://doi.org/10.1038/s41597-021-00893-z
Journal volume & issue: Vol. 8, no. 1
pp. 1 – 12

Abstract

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Measurement(s) Low Dose Computed Tomography of the Chest • feature extraction objective Technology Type(s) digital curation • image processing technique Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13526360

Published in Scientific Data

ISSN: 2052-4463 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/sdata/

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