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| Format: | Recurso digital |
| Langue: | |
| Publié: |
Zenodo
2026
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| Accès en ligne: | https://doi.org/10.5281/zenodo.18213306 |
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| _version_ | 1866901289511682048 |
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| author | Anonymous |
| author_facet | Anonymous |
| contents | <p>This archive contains two trained models used in the DigiECG pipeline for automated digitization of printed and mobile-captured 12-lead ECG records. The first model localizes the 12 ECG leads by predicting one bounding box per lead across diverse layouts, rotations, and imaging conditions. The second model performs pixel-level separation of ECG signal from background within each detected lead region, enabling accurate waveform extraction for downstream signal reconstruction and analysis.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18213306 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | digiecg_lead_detection_and_signal_segmentation_models Anonymous <p>This archive contains two trained models used in the DigiECG pipeline for automated digitization of printed and mobile-captured 12-lead ECG records. The first model localizes the 12 ECG leads by predicting one bounding box per lead across diverse layouts, rotations, and imaging conditions. The second model performs pixel-level separation of ECG signal from background within each detected lead region, enabling accurate waveform extraction for downstream signal reconstruction and analysis.</p> |
| title | digiecg_lead_detection_and_signal_segmentation_models |
| url | https://doi.org/10.5281/zenodo.18213306 |