TY - GEN
T1 - Detecting Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope via Deep Learning
AU - Li, Xueshen
AU - Gan, Yu
AU - Duan, David
AU - Yang, Xiao
N1 - Publisher Copyright:
© 2023 SPIE.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Deep learning
KW - Gastric motility disorders
KW - Magnetically controlled capsule endoscopy
KW - Medical image analysis
UR - http://www.scopus.com/inward/record.url?scp=85159642176&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159642176&partnerID=8YFLogxK
U2 - 10.1117/12.2646723
DO - 10.1117/12.2646723
M3 - Conference contribution
AN - SCOPUS:85159642176
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2023
A2 - Colliot, Olivier
A2 - Isgum, Ivana
T2 - Medical Imaging 2023: Image Processing
Y2 - 19 February 2023 through 23 February 2023
ER -