More slices, less truth: effects of different test-set design strategies for magnetic resonance image classification

AIM: To assess the effects of different test-set design strategies for magnetic resonance (MR) image classification using deep learning. METHODS: Error rates in 10 experimental settings were assessed. The performance of pretrained models and data augmentation were examined as possible contributing f...

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Detalles Bibliográficos
Autores principales: Glavaški, Mila, Velicki, Lazar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Croatian Medical Schools 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468729/
https://www.ncbi.nlm.nih.gov/pubmed/36046934
http://dx.doi.org/10.3325/cmj.2022.63.370

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468729/
https://www.ncbi.nlm.nih.gov/pubmed/36046934
http://dx.doi.org/10.3325/cmj.2022.63.370

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