Simulated MRI Artifacts: Testing Machine Learning Failure Modes

Objective. Seven types of MRI artifacts, including acquisition and preprocessing errors, were simulated to test a machine learning brain tumor segmentation model for potential failure modes. Introduction. Real-world medical deployments of machine learning algorithms are less common than the number o...

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Detalles Bibliográficos
Autores principales: Wang, Nicholas C., Noll, Douglas C., Srinivasan, Ashok, Gagnon-Bartsch, Johann, Kim, Michelle M., Rao, Arvind
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521705/
https://www.ncbi.nlm.nih.gov/pubmed/37850164
http://dx.doi.org/10.34133/2022/9807590

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521705/
https://www.ncbi.nlm.nih.gov/pubmed/37850164
http://dx.doi.org/10.34133/2022/9807590

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