Automated detection of pulmonary embolism from CT-angiograms using deep learning

BACKGROUND: The aim of this study was to develop and evaluate a deep neural network model in the automated detection of pulmonary embolism (PE) from computed tomography pulmonary angiograms (CTPAs) using only weakly labelled training data. METHODS: We developed a deep neural network model consisting...

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Detalles Bibliográficos
Autores principales: Huhtanen, Heidi, Nyman, Mikko, Mohsen, Tarek, Virkki, Arho, Karlsson, Antti, Hirvonen, Jussi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8919639/
https://www.ncbi.nlm.nih.gov/pubmed/35282821
http://dx.doi.org/10.1186/s12880-022-00763-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8919639/
https://www.ncbi.nlm.nih.gov/pubmed/35282821
http://dx.doi.org/10.1186/s12880-022-00763-z

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