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...

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Detalles Bibliográficos
Autores principales: Kasmanoff, Noah, Lee, Matthew D., Razavian, Narges, Lui, Yvonne W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Diagnostic Neuroradiology
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

Internet

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

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