Lane, E., Azarmehr, N., Jevsikov, J. et al. (4 more authors) (2021) Echocardiographic phase detection using neural networks. In: MIDL 2021 : Medical Imaging with Deep Learning, Proceedings. MIDL 2021 : Medical Imaging with Deep Learning, 07-09 Jul 2021, Lübeck, Germany (online). .
Abstract
Accurate identification of end-diastolic (ED) and end-systolic (ES) frames in echocardiographic cine loops is essential when measuring cardiac function. Manual selection by human experts is challenging and error prone. We present a deep neural network trained and tested on multi-centre patient data for accurate phase detection in apical four-chamber videos of arbitrary length, spanning several heartbeats, with performance indistinguishable from that of human experts.
Metadata
| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2021 The Authors. |
| Keywords: | Echocardiography; Cardiac imaging; Deep learning; Phase detection |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Clinical Dentistry (Sheffield) |
| Depositing User: | Symplectic Sheffield |
| Date Deposited: | 20 Aug 2021 13:49 |
| Last Modified: | 20 Aug 2021 13:49 |
| Published Version: | https://openreview.net/forum?id=uEuoKy2hUkm |
| Status: | Published |
| Refereed: | Yes |
| Related URLs: |
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