AIMC Topic: Esophageal Sphincter, Upper
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Application of deep learning technology for temporal analysis of videofluoroscopic swallowing studies.
Scientific reports
Oct 16, 2023
Temporal parameters during swallowing are analyzed for objective and quantitative evaluation of videofluoroscopic swallowing studies (VFSS). Manual analysis by clinicians is time-consuming, complicated and prone to human error during interpretation; ...
Deep Learning-Based Delineation of Head and Neck Organs at Risk: Geometric and Dosimetric Evaluation.
International journal of radiation oncology, biology, physics
Mar 2, 2019
PURPOSE: Organ-at-risk (OAR) delineation is a key step in treatment planning but can be time consuming, resource intensive, subject to variability, and dependent on anatomical knowledge. We studied deep learning (DL) for automated delineation of mult...
Calculation of upper esophageal sphincter restitution time from high resolution manometry data using machine learning.
Physiology & behavior
Aug 10, 2016
OBJECTIVE: After swallowing, the upper esophageal sphincter (UES) needs a certain amount of time to return from maximum pressure to the resting condition. Disturbances of sphincter function not only during the swallowing process but also in this phas...
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