Automatic and Fast Whole Heart Segmentation for 3D Reconstruction-Reference-Cited by-同舟云学术

Automatic and Fast Whole Heart Segmentation for 3D Reconstruction

Published:2022-05-28 Issue: Volume: Page:
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Container-title:2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)
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Author:

Zrira Nabila¹,Benmiloud Ibtissam²,Marzouki Kamal³,Farahat Zineb⁴,Zaimi Imane⁵,El Ghali Btihal⁶,El Midaoui Omar⁷,Megdiche Kawtar⁸,Ngote Nabil⁹

Affiliation:

1. Ecole Nationale Supérieure des Mines,ADOS Team, LISTD Laboratory,Rabat,Morocco

2. Ecole Nationale Supérieure des Mines,Rabat,Morocco

3. Medical Simulation Center of the Cheikh Zaid Foundation, and Cheikh Zaid Hospital,Rabat,Morocco

4. Ecole Nationale Supérieure des Mines,Medical Simulation Center of the Cheikh Zaid Foundation,Rabat,Morocco

5. Sultan Moulay Slimane University,Superior School of Technology,Khenifra,Morocco

6. Ecole Nationale Supérieure des Mines,ITQAN Team, LYRICA,Department of Data and Knowledge Engineering Information Sciences School (ESI),Rabat,Morocco

7. Ecole Nationale Supérieure des Mines,SmartiLab, Moroccan School of Engineering Sciences,Rabat,Morocco

8. Medical Simulation Center of the Cheikh Zaid Foundation,Rabat,Morocco

9. Abulcasis International University of Health Sciences,Ecole Nationale Supérieure des Mines,Rabat,Morocco

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9875397/9875429/09875773.pdf?arnumber=9875773

Reference26 articles.

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2. Right ventricle segmentation from cardiac MRI: A collation study

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4. U-net: Convolutional networks for biomedical image segmentation;ronneberger;International Conference on Medical Image Computing and Computer-Assisted Intervention,2015

5. Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features

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