1. Bogunovic, H., Venhuizen, F., Klimscha, S., Apostolopoulos, S., Bab-Hadiashar, A., et al.: RETOUCH: the retinal OCT fluid detection and segmentation benchmark and challenge. IEEE Trans. Med. Imaging 38(8), 1858–1874 (2019)
2. Bolte, J.A., et al.: Unsupervised domain adaptation to improve image segmentation quality both in the source and target domain. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 1404–1413 (2019)
3. Caron, M., et al.: Emerging properties in self-supervised vision transformers. In: IEEE International Conference on Computer Vision (ICCV), pp. 9650–9660 (2021)
4. Chaitanya, K., Erdil, E., Karani, N., Konukoglu, E.: Contrastive learning of global and local features for medical image segmentation with limited annotations. In: Advances in Neural Information Processing Systems (NeurIPS), vol. 33, pp. 12546–12558 (2020)
5. Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning (ICML), pp. 1597–1607 (2020)