Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction-Reference-Cited by-同舟云学术

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Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

Published:2019 Issue: Volume: Page:541-549
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Bai Wenjia,Chen Chen,Tarroni Giacomo,Duan Jinming,Guitton Florian,Petersen Steffen E.,Guo Yike,Matthews Paul M.,Rueckert Daniel

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-32245-8_60

Reference12 articles.

1. Bernard, O., et al.: Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis. IEEE Trans. Med. Imaging 37(11), 2514–2525 (2018)

2. Bai, W., et al.: Automated cardiovascular magnetic resonance image analysis with fully convolutional networks. J. Cardiovasc. Magn. Reson. 20(1), 65 (2018)

3. Tao, Q., et al.: Deep learning-based method for fully automatic quantification of left ventricle function from cine MR images. Radiology 290(1), 81–88 (2019)

4. Doersch, C., et al.: Multi-task self-supervised visual learning. In: ICCV (2017)

5. Gidaris, S., et al.: Unsupervised representation learning by predicting image rotations. In: ICLR (2018)

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