A deep learning-based system for bile duct annotation and station recognition in linear endoscopic ultrasound.

ABSTRACT:

Background

Detailed evaluation of bile duct (BD) is main focus during endoscopic ultrasound (EUS). The aim of this study was to develop a system for EUS BD scanning augmentation.

Methods

The scanning was divided into 4 stations. We developed a station classification model and a BD segmentation model with 10681 images and 2529 images, respectively. 1704 images and 667 images were applied to classification and segmentation internal validation. For classification and segmentation video validation, 264 and 517 videos clips were used. For man-machine contest, an independent data set contained 120 images was applied. 799 images from other two hospitals were used for external validation. A crossover study was conducted to evaluate the system effect on reducing difficulty in ultraso

SUBMITTER: Yao L 

PROVIDER: S-EPMC7921468 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature