Fluoroscopic image-driven deep learning model for predicting intussusception irreducibility during air enema in children
Abstract Background Accurate identification of irreducible intussusception during air enema is crucial for optimizing enema strategies. Current methods are limited by subjective interpretation and inconsistent clinical criteria. We developed a deep learning (DL) framework to objectively predict irre...
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| Główni autorzy: | , , , , , , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
BMC
2026-04-01
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| Seria: | BMC Medical Imaging |
| Hasła przedmiotowe: | |
| Dostęp online: | https://doi.org/10.1186/s12880-026-02385-1 |
| Etykiety: |
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