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        <datestamp>2025-07-21</datestamp>
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          <dc:identifier>https://doi.org/10.17045/STHLMUNI.26164570</dc:identifier>
          <dc:title xml:lang="en">X-ray microCT lizard brain data and labels. Trained network using Biomedisa with different number of training datasets.</dc:title>
          <dc:creator>https://orcid.org/0000-0002-7258-002X</dc:creator>
          <dc:creator>Yulia Dragunova</dc:creator>
          <dc:creator>https://orcid.org/0000-0001-5592-8963</dc:creator>
          <dc:subject xml:lang="en">Biological Sciences</dc:subject>
          <dc:subject xml:lang="sv">Biologi</dc:subject>
          <dc:description xml:lang="en">28_pbo24_100kV9WLE2Obj0p4xBin2t1sP801_recon.zip: X-ray tomography data of a lizard head (Podarcis bocagei) using Zeiss Xradia Versa 520 at Stockholm University Brain Imaging Center (SUBIC).

SegmFromDLalgorithm.zip: X-ray microCT (microcomputed tomography) data of lizard heads, cropped down to brain part, and the corresponding labels of brain regions segmented by deep learning algorithm.

SegmForDLmanual.zip: X-ray microCT data of lizard heads, cropped down to brain part, and the corresponding labels of brain regions segmented semi-manually used as training dataset for deep learning.

06_recon.zip: an example of original X-ray microCT data of a lizard head before cropping.

The trained networks below can be used in Biomedisa https://biomedisa.info :

NetworkTrainedWith5data.tar.h5: trained network using 5 datasets

NetworkTrainedWith7data.tar.h5: trained network using 7 datasets

NetworkTrainedWith9data.tar.h5: trained network using 9 datasets

NetworkTrainedWith11data.tar.h5: trained network using 11 datasets</dc:description>
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          <dc:publisher xml:lang="en">Stockholm University</dc:publisher>
          <dc:publisher xml:lang="sv">Stockholms universitet</dc:publisher>
          <dc:date>2025-07-21T00:00:00Z</dc:date>
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