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

• Main Authors: Hoon Ko (Author), Jimi Huh (Author), Kyung Won Kim (Author), Heewon Chung (Author), Yousun Ko (Author), Jai Keun Kim (Author), Jei Hee Lee (Author), Jinseok Lee (Author)
• Format: Book
• Published: JMIR Publications, 2022-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

BackgroundDetection 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. Objec...