Refining Skip Connections by Fusing Multi-scaled Context in Neural Network for Cardiac MR Image Segmentation-Reference-Cited by-同舟云学术

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Refining Skip Connections by Fusing Multi-scaled Context in Neural Network for Cardiac MR Image Segmentation

Published:2021 Issue: Volume: Page:47-57
ISSN:1860-949X
Container-title:Soft Computing: Biomedical and Related Applications
language:
Short-container-title:

Author:

Nguyen Nhu-Toan,Trinh Minh-Nhat,Tran Thi-Thao,Pham Van-Truong

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-76620-7_4

Reference20 articles.

1. Tran, P.V.: A fully convolutional neural network for cardiac segmentation in short-axis MRI. arXiv preprint arXiv:1604.00494 (2016)

2. Shyu, K.K., Pham, V.T., Tran, T.T., Lee, P.L.: Unsupervised active contours driven by density distance and local fitting energy with applications to medical image segmentation. Mach. Vis. Appl. 23(6), 1159–1175 (2012)

3. Tran, T.T., Pham, V.T., Lin, C., Yang, H.W., Wang, Y.H., Shyu, K.K., Tseng, W.Y., Su, M.Y., Lin, L.Y., Lo, M.T.: Empirical mode decomposition and monogenic signal based approach for quantification of myocardial infarction from MR images. IEEE J. Biomed. Health Inform. 23(2), 731–743 (2019)

4. Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 234–241. Springer (2015)

5. Badrinarayanan, V., Kendall, A., Cipolla, R.: SegNet: a deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39(12), 2481–2495 (2017)

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1. Axial Attention MLP-Mixer: A New Architecture for Image Segmentation;2022 IEEE Ninth International Conference on Communications and Electronics (ICCE);2022-07-27

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