An active learning approach to train a deep learning algorithm for tumor segmentation from brain MR images

PURPOSE: This study focuses on assessing the performance of active learning techniques to train a brain MRI glioma segmentation model. METHODS: The publicly available training dataset provided for the 2021 RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge was used in this study, consisting...

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Detalles Bibliográficos
Autores principales: Boehringer, Andrew S., Sanaat, Amirhossein, Arabi, Hossein, Zaidi, Habib
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10449747/
https://www.ncbi.nlm.nih.gov/pubmed/37620554
http://dx.doi.org/10.1186/s13244-023-01487-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10449747/
https://www.ncbi.nlm.nih.gov/pubmed/37620554
http://dx.doi.org/10.1186/s13244-023-01487-6

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