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Supervised machine learning quality control for magnetic resonance artifacts in neonatal data sets
Quality control (QC) of brain magnetic resonance images (MRI) is an important process requiring a significant amount of manual inspection. Major artifacts, such as severe subject motion, are easy to identify to naïve observers but lack automated identification tools. Clinical trials involving motion...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley & Sons, Inc.
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6588009/ https://www.ncbi.nlm.nih.gov/pubmed/30467922 http://dx.doi.org/10.1002/hbm.24449 |