Automatic Image Selection Model Based on Machine Learning for Endobronchial Ultrasound Strain Elastography Videos.

ABSTRACT:

Background

Endoscopic ultrasound (EBUS) strain elastography can diagnose intrathoracic benign and malignant lymph nodes (LNs) by reflecting the relative stiffness of tissues. Due to strong subjectivity, it is difficult to give full play to the diagnostic efficiency of strain elastography. This study aims to use machine learning to automatically select high-quality and stable representative images from EBUS strain elastography videos.

Methods

LNs with qualified strain elastography videos from June 2019 to November 2019 were enrolled in the training and validation sets randomly at a quantity ratio of 3:1 to train an automatic image selection model using machine learning algorithm. The strain elastography videos in December 2019 were used as the test set, from which three repre

SUBMITTER: Zhi X 

PROVIDER: S-EPMC8201408 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature