Invert‐U‐Net DNN segmentation model for MRI cardiac left ventricle segmentation-Reference-Cited by-同舟云学术

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Invert‐U‐Net DNN segmentation model for MRI cardiac left ventricle segmentation

Published:2018-10-18 Issue:16 Volume:2018 Page:1463-1467
ISSN:2051-3305
Container-title:The Journal of Engineering
language:en
Short-container-title:J. eng.

Author:

Cong Chao¹,Zhang Hongmin¹

Affiliation:

1. Chongqing University of TechnologyChongqingPeople's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2018.8302

Reference16 articles.

1. Heart disease and stroke statistics‐2016 update: a report from the American Heart Association;Mozaffarian D.;Circulation,2016

2. Imaging techniques for cardiac strain and deformation: comparison of echocardiography, cardiac magnetic resonance and cardiac computed tomography;Tee M.;Expert Rev. Cardiovasc. Ther.,2013

3. LongJ. ShelhamerE. DarrellT.: ‘Fully convolutional networks for semantic segmentation’.2015 IEEE Conf. on Computer Vision and Pattern Recognition Boston USA June 2015 pp.3431–3440

4. A combined deep‐learning and deformable‐model approach to fully automatic segmentation of the left ventricle in cardiac MRI;Avendi M.R.;Med. Image Anal.,2016

5. TranP.V.: ‘A fully convolutional neural network for cardiac segmentation in short‐axis MRI’ arXiv preprint arXiv:1604.00494 2016

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