A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation

BACKGROUND: Detection and quantification of intra-abdominal free fluid (ie, ascites) on computed tomography (CT) images are essential processes for finding emergent or urgent conditions in patients. In an emergency department, automatic detection and quantification of ascites will be beneficial. OBJ...

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Detalles Bibliográficos
Autores principales: Ko, Hoon, Huh, Jimi, Kim, Kyung Won, Chung, Heewon, Ko, Yousun, Kim, Jai Keun, Lee, Jei Hee, Lee, Jinseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764611/
https://www.ncbi.nlm.nih.gov/pubmed/34982041
http://dx.doi.org/10.2196/34415

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764611/
https://www.ncbi.nlm.nih.gov/pubmed/34982041
http://dx.doi.org/10.2196/34415

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