Clinical Research on a Novel Deep-learning Based System in Pancreatic Endoscopic Ultrasound Scanning

In this study, pancreatic endoscopic ultrasound scanning videos and images will be collected. First of all, an artificial intelligence system based on deep learning for the navigation and quality control of pancreatic endoscopic ultrasonography will be established. Secondly, the artificial intelligence system will be used to identify the site and anatomical structure of the pancreatic ultrasound endoscopy, and the results of the artificial intelligence system's station recognition will be compared with the results of the endoscopist's station recognition. Finally, the completeness of standard sites and scanning time of endoscopic-assisted and non-assisted AI systems were compared.

Inclusion criteria

• 1. Age ≥18 years old, <80 years old 2.Patients who need endoscopic ultrasonography of pancreas; 3. Agree to participate in this study and sign the informed consent form.

Exclusion criteria

• Subjects who meet any of the following criteria cannot be selected for this trial:

First. The patient's physical condition does not meet the requirements of conventional endoscopic ultrasonography:

• Poor physical condition, including hemoglobin ≤8.0g/dl, severe cardiopulmonary insufficiency, etc.
• Anesthesia assessment failed
• Pregnancy or breastfeeding
• In the acute stage of chemical and corrosive injury, it is very easy to cause perforation
• Recent acute coronary syndrome or clinically unstable ischemic heart attack
• Heart disease patients with right-to-left shunt, patients with severe pulmonary hypertension (pulmonary artery pressure> 90mmHg),patients with uncontrolled systemic hypertension and patients with adult respiratory distress syndrome.

Second. Disagree to participate in this study.

Third. There are other problems that do not meet the requirements of this research or that affect the results of the research:

• Pancreatic disease has undergone surgery or radiotherapy and chemotherapy beforehand;
• Mental illness, drug addiction, inability to express themselves or other diseases that may affect follow-up.