A Right Ventricle Segmentation Method based on U-Net with Weighted Convolution and Dense Connection-Reference-Cited by-同舟云学术

A Right Ventricle Segmentation Method based on U-Net with Weighted Convolution and Dense Connection

Published:2020-04-23 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing
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Author:

Miao Yu¹,Shen Chun-Xia¹,Shi Wei-Li¹,Zhang Ke¹,Jiang Zhen-Gang¹,Yang Hua-Min¹

Affiliation:

1. School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3399637.3399652

Reference22 articles.

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4. COCOSCO C A NIESSEN W J NETSCH T etal Automatic image-driven segmentation of the ventricles in cardiac cine MRI[J].Journal of Magnetic resonance Imaging 2008 28(2): 366--374. COCOSCO C A NIESSEN W J NETSCH T et al. Automatic image-driven segmentation of the ventricles in cardiac cine MRI[J].Journal of Magnetic resonance Imaging 2008 28(2): 366--374.

5. Mahapatra D. Cardiac Image Segmentation from Cine Cardiac MRI Using Graph Cuts and Shape Priors[J]. Journal of digital imaging 2013 26(4):721--730. Mahapatra D. Cardiac Image Segmentation from Cine Cardiac MRI Using Graph Cuts and Shape Priors[J]. Journal of digital imaging 2013 26(4):721--730.

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