Unsupervised Domain Adaptation for Vertebrae Detection and Identification in 3D CT Volumes Using a Domain Sanity Loss

A variety of medical computer vision applications analyze 2D slices of computed tomography (CT) scans, whereas axial slices from the body trunk region are usually identified based on their relative position to the spine. A limitation of such systems is that either the correct slices must be extracte...

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Detalles Bibliográficos
Autores principales: Sager, Pascal, Salzmann, Sebastian, Burn, Felice, Stadelmann, Thilo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410021/
https://www.ncbi.nlm.nih.gov/pubmed/36005465
http://dx.doi.org/10.3390/jimaging8080222

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410021/
https://www.ncbi.nlm.nih.gov/pubmed/36005465
http://dx.doi.org/10.3390/jimaging8080222

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