Deep learning-based automatic identification model of main pancreatic duct in intraoperative ultrasonography

P1.245. Real-Time AI-Based Thoracic Duct Recognition During Thoracoscopic Esophagectomy

Esophageal Cancer: Surgical Treatment of Esophageal Cancer – technique Thoracic duct injury during thoracoscopic esophagectomy may result in postoperative chylothorax, a serious complication associated with increased morbidity. However, intraoperative identification of the thoracic duct remains challenging...

Automated recognition of critical anatomical structures in laparoscopic cholecystectomy using artificial intelligence

Despite the widespread use of minimally invasive surgery, bile duct injury (BDI) remains a significant complication of laparoscopic cholecystectomy (LC). Accurate identification of the common bile duct (CBD) and common hepatic duct (CHD) is critical for preventing BDI. This study aimed to develop and evaluate a dee...

Automated Detection of Extrahepatic Bile Duct Stones on Intraoperative Cholangiography Using Deep Learning

Objective: To evaluate the case-level performance of deep-learning segmentation models for detecting extrahepatic bile duct stones on representative intraoperative cholangiography images (IOC) and to characterize the completeness of individual-stone localization. Background: Retained bile duct stones can cause biliary...

Deep learning-based automated identification of papillary bladder cancer from endoscopic still images using SE-ResNeXt-50

Evaluation of Computer‐aided Detection for Identifying Missed Gastric Cancer After Endoscopic Submucosal Dissection

No significant difference in sensitivity was observed between CADe and endoscopist detection for MGCs after ESD, and the absolute sensitivity remained low, so further improvements are needed before clinical implementation of CADe as a double‐checking tool.

Evaluation of gastric cancer using artificial intelligence iterative reconstruction on abdominal CT: image quality and diagnostic accuracy.

PURPOSE To investigate the clinical performance of a novel deep-learning based image reconstruction algorithm, namely artificial intelligence iterative reconstruction (AIIR), for assessing gastric cancer (GC) on CT. MATERIALS AND METHODS We prospectively enrolled 132 GC patients without history of treatment, all of w...