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Deep multi-task learning and random forest for series classification by pulse sequence type and orientation
PURPOSE: Increasingly complex MRI studies and variable series naming conventions reveal limitations of rule-based image routing, especially in health systems with multiple scanners and sites. Accurate methods to identify series based on image content would aid post-processing and PACS viewing. Recen...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9361920/ https://www.ncbi.nlm.nih.gov/pubmed/35906437 http://dx.doi.org/10.1007/s00234-022-03023-7 |