Detecting human gastric peristalsis using magnetically controlled capsule endoscope via deep learning

Xueshen Li; Yu Gan; David Duan; Xiao Yang

doi:10.1117/12.2646723

3 April 2023 Detecting human gastric peristalsis using magnetically controlled capsule endoscope via deep learning

Xueshen Li, Yu Gan, David Duan, Xiao Yang

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124641F (2023) https://doi.org/10.1117/12.2646723
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

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.

Citation Download Citation

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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