Deep neural networks for ECG-free cardiac phase and end-diastolic frame detection on coronary angiographies

Author:

Ciusdel CostinORCID,Turcea Alexandru,Puiu Andrei,Itu LucianORCID,Calmac Lucian,Weiss Emma,Margineanu Cornelia,Badila Elisabeta,Berger Martin,Redel Thomas,Passerini Tiziano,Gulsun Mehmet,Sharma Puneet

Funder

Ministery of Research and Innovation, CNCS - UEFISCDI

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference48 articles.

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2. Inherited progressive cardiac conduction disorders;Baruteau;Curr. Opin. Cardiol.,2015

3. A machine-learning approach for enhancing resting state measurements for the functional assessment of coronary lesions - initial validation on a real-world single center population;Calmac;Proc EuroPCR,2018

4. BioSPPy - Biosignal Processing in Python;Carreiras,2015

5. Angiography-based machine learning for predicting fractional flow reserve in intermediate coronary artery lesions;Cho;J. Am. Heart Assoc.,2019

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