Real-time deep learning-based image guiding and automated left ventricular measurements to reduce test-retest variability.

ABSTRACT:

Aims

To evaluate the effect of combining real-time deep learning (DL)-based guiding and automated measurements of left ventricular (LV) volumetric measurements and strain.

Methods and results

Patients (n=47) with mixed cardiac pathology were examined by two sonographers and one reference cardiologist. A real-time DL guiding tool to avoid LV foreshortening was used by one sonographer only per patient. Automated DL-based measurements from the sonographer using the guiding tool were paired with automated measurements from the reference cardiologist (artificial intelligence (AI)-assisted echocardiography), while manual measurements from the sonographer not using the guiding tool were paired with manual measurements from the reference cardiologist (standard echocardiography). The

SUBMITTER: Pettersen H 

PROVIDER: S-EPMC12699943 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature