Automated deep neural network-based identification, localization, and tracking of cardiac structures for ultrasound-guided interventional surgery.

ABSTRACT:

Background

The increase in the use of ultrasound-guided interventional therapy for cardiovascular diseases has increased the importance of intraoperative real-time cardiac ultrasound image interpretation. We thus aimed to develop a deep learning-based model to accurately identify, localize, and track the critical cardiac structures and lesions (9 kinds in total) and to validate the algorithm's performance using independent data sets.

Methods

This diagnostic study developed a deep learning-based model using data collected from Fuwai Hospital between January 2018 and June 2019. The model was validated with independent French and American data sets. In total, 17,114 cardiac structures and lesions were used to develop the algorithm. The model findings were compared with those of

SUBMITTER: Liu Z 

PROVIDER: S-EPMC10183525 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature