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Poster + Paper
3 April 2023 Detecting human gastric peristalsis using magnetically controlled capsule endoscope via deep learning
Author Affiliations +
Conference Poster
Abstract
Gastric motility disorders are caused by abnormal muscle contractions which may impede the digestive process. Traditional approaches for evaluating human gastric motility have limitations, including discomfort, use of sedation, risk of radiation exposure, and confusion in interpretation. Magnetically controlled capsule endoscopy (MCCE) provides a new way to evaluate human gastric with the advantages of comfort, safety, and no anesthesia. In this paper, we develop deep learning algorithms to detect human gastric waves captured by MCCE. We demonstrate promising experimental results both qualitatively and quantitatively. Our methods have great potential to assist in the diagnosis of human gastric disease by evaluating gastric motility.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xueshen Li, Yu Gan, David Duan, and Xiao Yang "Detecting human gastric peristalsis using magnetically controlled capsule endoscope via deep learning", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124641F (3 April 2023); https://doi.org/10.1117/12.2646723
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KEYWORDS
Electronic filtering

Video

Education and training

Cameras

Diseases and disorders

Deep learning

Algorithm development

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