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        <datestamp>2020-09-17</datestamp>
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          <dc:identifier>https://doi.org/10.5281/zenodo.4030660</dc:identifier>
          <dc:title xml:lang="en">CSAW-S</dc:title>
          <dc:creator>https://orcid.org/0000-0003-1401-3497</dc:creator>
          <dc:creator>Hernandez, Albert Bou I</dc:creator>
          <dc:creator>Liu, Yue</dc:creator>
          <dc:creator>Dembrower, Karin</dc:creator>
          <dc:creator>Miranda, Gisele</dc:creator>
          <dc:creator>Konuk, Emir</dc:creator>
          <dc:creator>Fredin Haslum, Johan</dc:creator>
          <dc:creator>Zouzos, Athanasios</dc:creator>
          <dc:creator>Lindholm, Peter</dc:creator>
          <dc:creator>Strand, Fredrik</dc:creator>
          <dc:creator>Smith, Kevin</dc:creator>
          <dc:subject xml:lang="en">Cancer and Oncology</dc:subject>
          <dc:subject xml:lang="sv">Cancer och onkologi</dc:subject>
          <dc:description xml:lang="en">The CSAW-S is a curated dataset containing mammography images with annotations of breast cancer and breast anatomy from experts and non-experts. It contains mammography screenings from 172 different patients with annotations for semantic segmentation. Additional information about our paper and the source code can be found here.

If you use this dataset please cite our work Adding seemingly uninformative labels helps in low data regimes.</dc:description>
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          <dc:publisher xml:lang="en">Royal Institute of Technology</dc:publisher>
          <dc:publisher xml:lang="sv">Kungliga Tekniska högskolan</dc:publisher>
          <dc:date>2020-09-16T00:00:00Z</dc:date>
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