Brain stroke lesion segmentation using consistent perception generative adversarial network-Reference-Cited by-同舟云学术

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Brain stroke lesion segmentation using consistent perception generative adversarial network

Published:2022-03-06 Issue:11 Volume:34 Page:8657-8669
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Wang Shuqiang,Chen Zhuo,You Senrong,Wang Bingchuan,Shen Yanyan,Lei Baiying

Funder

National Natural Science Foundation of China

International Science and Technology Cooperation Programme

Distinguished Young Scholars Fund of Guangdong

National Natural Science Foundations of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-021-06816-8.pdf

Reference63 articles.

1. Abraham N, Khan NM (2019) A novel focal tversky loss function with improved attention u-net for lesion segmentation. In: 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 683–687. IEEE

2. Bang D, Shim H (2018) Improved training of generative adversarial networks using representative features. arXiv preprint arXiv:1801.09195

3. Baur C, Albarqouni S, Navab N (2017) Semi-supervised deep learning for fully convolutional networks. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 311–319. Springer

4. Chen LC, Zhu Y, Papandreou G, Schroff F, Adam H (2018) Encoder-decoder with atrous separable convolution for semantic image segmentation. In: Proceedings of the European conference on computer vision (ECCV), pp. 801–818. Cham

5. Chen MT, Mahmood F, Sweer JA, Durr NJ (2019) Ganpop: generative adversarial network prediction of optical properties from single snapshot wide-field images. IEEE Trans Med Imag 39:1988

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