Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction

OBJECTIVES: Computed tomography (CT)–based bronchial parameters correlate with disease status. Segmentation and measurement of the bronchial lumen and walls usually require significant manpower. We evaluate the reproducibility of a deep learning and optimal-surface graph-cut method to automatically...

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Detalles Bibliográficos
Autores principales: Dudurych, Ivan, Garcia-Uceda, Antonio, Petersen, Jens, Du, Yihui, Vliegenthart, Rozemarijn, de Bruijne, Marleen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Technical Developments
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10511366/
https://www.ncbi.nlm.nih.gov/pubmed/37071168
http://dx.doi.org/10.1007/s00330-023-09615-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10511366/
https://www.ncbi.nlm.nih.gov/pubmed/37071168
http://dx.doi.org/10.1007/s00330-023-09615-y

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