Digital Pathology Dataset for Breast Cancer Diagnosis
<p>Links to code:<br><a href="https://zenodo.org/records/14294426">Tissue Region Segmentation Code</a><br>This dataset comprises high-quality <strong>immunohistochemistry (IHC)</strong> and <strong>Haematoxylin and Eosin (H&E)</strong> whole slide images (WSIs) of breast tissues, provided in <strong>.svs format</strong>.</p> <ul> <li>The <strong>IHC dataset</strong> (labeled as <em>BAU_IHC</em>) consists of <strong>55 zip files</strong>, each containing 2–3 WSIs, for a total of <strong>163 slides</strong>.</li> <li>The <strong>H&E dataset</strong> (labeled as <em>BAU_HE</em>) consists of <strong>36 zip files</strong>, each containing 2 WSIs, for a total of <strong>72 slides</strong>.</li> </ul> <p>The data were collected from <strong>Bahçeşehir University Medical School</strong> and are intended for research in <strong>histopathology </strong>and <strong>computational pathology</strong>.</p> <p>This study was approved by the <strong>Bahçeşehir University Clinical Research Institutional Review Board</strong> (Approval No: 2022-10/03).</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 4