| _version_ | 1866902184834105344 |
|---|---|
| author | University of Sheffield |
| author_facet | University of Sheffield |
| contents | <h1>Description</h1> <p>A heterogeneous collection of source data used for testing or debugging miblab code.</p> <h1>Datasets</h1> <h3><strong>test_data_post_contrast_dixon</strong></h3> <p>This dataset contains anonymized MRI Dixon sequences acquired post-contrast for use in testing kidney segmentation algorithms. The data includes four image series derived from the Dixon method:</p> <ul> <li>In-Phase</li> <li>Out-of-Phase</li> <li>Water</li> <li>Fat</li> </ul> <p>The dataset was selected to support deep learning model validation for automated kidney segmentation in post-contrast abdominal MRI scans.</p> <p>Contents: 1 ZIP file containing 4 DICOM series:</p> <ul> <li>Dixon_post_contrast_in_phase</li> <li>Dixon_post_contrast_out_phase</li> <li>Dixon_post_contrast_water</li> <li>Dixon_post_contrast_fat</li> </ul> <p>The data presented in this record were generated as part of the <a href="https://www.beat-dkd.eu/" target="_blank" rel="noopener">BEAt-DKD</a> (Biomarker Enterprise to Attack Diabetic Kidney Disease) project, which aims to improve understanding and treatment of diabetic kidney disease. </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15489381 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | MIBLAB test data University of Sheffield <h1>Description</h1> <p>A heterogeneous collection of source data used for testing or debugging miblab code.</p> <h1>Datasets</h1> <h3><strong>test_data_post_contrast_dixon</strong></h3> <p>This dataset contains anonymized MRI Dixon sequences acquired post-contrast for use in testing kidney segmentation algorithms. The data includes four image series derived from the Dixon method:</p> <ul> <li>In-Phase</li> <li>Out-of-Phase</li> <li>Water</li> <li>Fat</li> </ul> <p>The dataset was selected to support deep learning model validation for automated kidney segmentation in post-contrast abdominal MRI scans.</p> <p>Contents: 1 ZIP file containing 4 DICOM series:</p> <ul> <li>Dixon_post_contrast_in_phase</li> <li>Dixon_post_contrast_out_phase</li> <li>Dixon_post_contrast_water</li> <li>Dixon_post_contrast_fat</li> </ul> <p>The data presented in this record were generated as part of the <a href="https://www.beat-dkd.eu/" target="_blank" rel="noopener">BEAt-DKD</a> (Biomarker Enterprise to Attack Diabetic Kidney Disease) project, which aims to improve understanding and treatment of diabetic kidney disease. </p> |
| title | MIBLAB test data |
| url | https://doi.org/10.5281/zenodo.15489381 |