Convolutional neural network for brachial plexus segmentation at the interscalene level.

ABSTRACT:

Background

Regional anesthesia with ultrasound-guided brachial plexus block is widely used for patients undergoing shoulder and upper limb surgery, but needle misplacement can result in complications. The purpose of this study was to develop and validate a convolutional neural network (CNN) model for segmentation of the brachial plexus at the interscalene level.

Methods

This prospective study included patients who underwent ultrasound-guided brachial plexus block in the Anesthesiology Department of Beijing Jishuitan Hospital between October 2019 and June 2022. A Unet semantic segmentation model was developed to train the CNN to identify the brachial plexus features in the ultrasound images. The degree of overlap between the predicted segmentation and ground truth segmentatio

SUBMITTER: Xi Y 

PROVIDER: S-EPMC10773123 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature