Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes-Reference-Cited by-同舟云学术

Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes

Published:2017 Issue: Volume: Page:302-310
ISSN:0302-9743
Container-title:Medical Image Computing and Computer Assisted Intervention − MICCAI 2017
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Author:

Abdi Amir H.,Luong Christina,Tsang Teresa,Jue John,Gin Ken,Yeung Darwin,Hawley Dale,Rohling Robert,Abolmaesumi Purang

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-66179-7_35

Reference14 articles.

1. Abdi, A.H., et al.: Automatic quality assessment of apical four-chamber echocardiograms using deep convolutional neural networks. In: Proceedings of SPIE, vol. 10133, pp. 101330S–101330S-7 (2017)

2. Lecture Notes in Computer Science;H Chen,2016

3. Chollet, F.: Keras (2015). https://github.com/fchollet/keras

4. Donahue, J., et al.: Long-term recurrent convolutional networks for visual recognition and description. IEEE Trans. Pattern Anal. Mach. Intell. 39(4), 677–691 (2017)

5. Lecture Notes in Computer Science;N El-Zehiry,2013

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