Real-Time Identification System of Magnetically Controlled Capsule Endoscopy Using Artificial Intelligence

Launched by CHANGHAI HOSPITAL · Dec 16, 2019

Keywords

ClinConnect Summary

Magnetically controlled capsule endoscopy (MCE) has been used in clinical practice for gastric examination, with high sensitivity and specificity of 90.4% and 94.7%, respectively.

Therefore, a real-time auxiliary system based on convolutional neural network deep learning framework was developed to assist clinicians to improve the quality in MCE examinations.

Patients referred for magnetically controlled capsule endoscopy (MCE) in the participating center were prospectively enrolled. After passage through the esophagus, physician will finish the gastric examination under magnetic steering ...

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • With or without gastrointestinal complaints
• • Scheduled to undergo a capsule endoscopy for both stomach and small bowel
• • Signed the informed consents before joining this study
• Exclusion Criteria:
• • Dysphagia or symptoms of gastric outlet obstruction, suspected or known intestinal stenosis, overt gastrointestinal bleeding, history of upper gastrointestinal surgery or abdominal surgery altering gastrointestinal anatomy
• • Refused abdominal surgery to take out the capsule in case of capsule retention
• • Implanted pacemaker, except the pacemaker is compatible with MRI
• • Other implanted electromedical devices or magnetic metal foreign bodies
• • Pregnancy or suspected pregnancy