- Keywords: Cardiac imaging, Tissue Doppler Echocardiography, Deep learning
- TL;DR: Deep learning model, trained and tested on Doppler strips of arbitrary length, for rapid beat detection and Cartesian coordinate localisation of peak velocities.
- Abstract: Tissue Doppler Imaging is an essential echocardiographic technique for the non-invasive assessment of myocardial blood velocity. Interpretation by trained experts is time-consuming and disruptive to workflow. This study presents an automated deep learning model, trained and tested on Doppler strips of arbitrary length, capable of rapid beat detection and Cartesian coordinate localisation of peak velocities with accuracy indistinguishable from human experts, but with greater speed.
- Registration: I acknowledge that acceptance of this work at MIDL requires at least one of the authors to register and present the work during the conference.
- Authorship: I confirm that I am the author of this work and that it has not been submitted to another publication before.
- Paper Type: novel methodological ideas without extensive validation
- Primary Subject Area: Transfer Learning and Domain Adaptation
- Secondary Subject Area: Detection and Diagnosis
- Confidentiality And Author Instructions: I read the call for papers and author instructions. I acknowledge that exceeding the page limit and/or altering the latex template can result in desk rejection.