Quantifying Valve Regurgitation Using 3-D Doppler Ultrasound Images and Deep Learning-Reference-Cited by-同舟云学术

Quantifying Valve Regurgitation Using 3-D Doppler Ultrasound Images and Deep Learning

Published:2022-12 Issue:12 Volume:69 Page:3317-3326
ISSN:0885-3010
Container-title:IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
language:
Short-container-title:IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

Author:

Wifstad Sigurd Vangen¹^ORCID,Lovstakken Lasse¹^ORCID,Avdal Jorgen¹^ORCID,Berg Erik Andreas Rye¹^ORCID,Torp Hans¹^ORCID,Grenne Bjornar¹^ORCID,Fiorentini Stefano¹^ORCID

Affiliation:

1. Center for Innovative Ultrasound Solutions, Norwegian University of Science and Technology, Trondheim, Norway

Funder

Centre for Innovative Ultrasound Solutions (CIUS), a centre for research-based innovation appointed by the Norwegian Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/58/9963905/09933481.pdf?arnumber=9933481

Reference35 articles.

1. Highlighting nerves and blood vessels for ultrasound-guided axillary nerve block procedures using neural networks

2. A Threshold Selection Method from Gray-Level Histograms

3. An iterative technique for the rectification of observed distributions

4. Deep Residual Learning for Image Recognition

5. Fast Flow-Line-Based Analysis of Ultrasound Spectral and Vector Velocity Estimators

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