Automated identification of MRI series using a hierarchical modular machine-learning pipeline
Abstract Objective The volume and diversity of large MR imaging datasets require efficient automated labelling tools for cataloguing MR series, as manual annotation is impractical and costly. However, relying on DICOM header fields alone is unreliable because sequence descriptors are heterogeneous a...
I tiakina i:
| Ngā kaituhi matua: | , , , , |
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| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
SpringerOpen
2026-05-01
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| Rangatū: | European Radiology Experimental |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1186/s41747-026-00740-z |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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