Prediction of glioma-subtypes: comparison of performance on a DL classifier using bounding box areas versus annotated tumors

BACKGROUND: For brain tumors, identifying the molecular subtypes from magnetic resonance imaging (MRI) is desirable, but remains a challenging task. Recent machine learning and deep learning (DL) approaches may help the classification/prediction of tumor subtypes through MRIs. However, most of these...

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Detalles Bibliográficos
Autores principales: Ali, Muhaddisa Barat, Gu, Irene Yu-Hua, Lidemar, Alice, Berger, Mitchel S., Widhalm, Georg, Jakola, Asgeir Store
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118766/
https://www.ncbi.nlm.nih.gov/pubmed/35590389
http://dx.doi.org/10.1186/s42490-022-00061-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118766/
https://www.ncbi.nlm.nih.gov/pubmed/35590389
http://dx.doi.org/10.1186/s42490-022-00061-3

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