Image segmentation using improved U-Net model and convolutional block attention module based on cardiac magnetic resonance imaging-Reference-Cited by-同舟云学术

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Image segmentation using improved U-Net model and convolutional block attention module based on cardiac magnetic resonance imaging

Published:2024-03 Issue:1 Volume:17 Page:100816
ISSN:1687-8507
Container-title:Journal of Radiation Research and Applied Sciences
language:en
Short-container-title:Journal of Radiation Research and Applied Sciences

Author:

Ye Yuguang,Chen Yusi,Wang Ronghua,Zhu Daxin,Huang Yifeng,Huang Ying,Liu Jiaxing,Chen Yijie,Shi Jianshe,Ding Bijiao,Xiahou Jianbing

Publisher

Elsevier BV

Reference31 articles.

1. Automatic segmentation and cardiopathy classification in cardiac MRI images based on deep neural networks;Chang,2018

2. Dynamic ReLU;Chen,2020

3. Retinal blood vessel segmentation based on dense U-net;Fu;Journal of Neijiang Normal University,2021

4. Brain tumor MR image segmentation based on improved U-net model;Fu;Journal of Xihua Normal University (Natural Science Edition),2021

5. GNNIUGnet: Precise segmentation neural network of left ventricular contours for MRI images based on group normalization and nearest interpolation;Gao;Computer Science,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A combination network based on graph modules for cardiac segmentation;Journal of Radiation Research and Applied Sciences;2024-06

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