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        <identifier>oai:researchdata.se:doi-10-17044-scilifelab-12771614/0</identifier>
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          <dc:identifier>https://doi.org/10.17044/SCILIFELAB.12771614</dc:identifier>
          <dc:title xml:lang="en">HASTE miniTEM Example Images</dc:title>
          <dc:creator>Ben Blamey</dc:creator>
          <dc:creator>Ida-Maria Sintorn</dc:creator>
          <dc:subject xml:lang="en">Medical and Health Sciences</dc:subject>
          <dc:subject xml:lang="sv">Medicin och hälsovetenskap</dc:subject>
          <dc:description xml:lang="en">Series of images of a sample of kidney tissue captured from the miniTEM (a 25keV transmission electron microscope) at Vironova offices in Stockholm (2019-02-04), for purposes of testing software related to the HASTE project (http://haste.research.it.uu.se/).
The dataset consists of 759 8-bit greyscale PNG images.

Used in this publication (and others):
Resource- and Message Size-Aware Scheduling of Stream Processing at the Edge with application to Realtime MicroscopyBen Blamey, Ida-Maria Sintorn, Andreas Hellander, Salman Toorhttps://arxiv.org/abs/1912.09088
Also"Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit, GigaScience, Volume 10, Issue 3, March 2021, giab018, https://doi.org/10.1093/gigascience/giab018</dc:description>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
          <dc:publisher xml:lang="en">Uppsala University</dc:publisher>
          <dc:publisher xml:lang="sv">Uppsala universitet</dc:publisher>
          <dc:date>2020-08-07T00:00:00Z</dc:date>
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