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English Information

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Authors
# Name
1 Graciella Favoreto(graciellafavoreto@usp.br)
2 Marcel Koenigkam-Santos(marcelk46@fmrp.usp.br)
3 Agma Traina(agma@icmc.usp.br)

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Reference
# Reference
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2 Candemir, S. et al. (2013). Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration. IEEE transactions on medical imaging, 33(2):577–590.
3 Chen, Y., , et al. (2023). Ldanet: Automatic lung parenchyma segmentation from ct images. Computers in Biology and Medicine, 155:106659.
4 Chowdhury, M. E. H. et al. (2020). Can ai help in screening viral and covid-19 pneumonia? IEEE Access, 8:132665–132676
5 Full, P. M. et al. (2021). Studying robustness of semantic segmentation under domain shift in cardiac mri. In Puyol Anton, E., Pop, M., Sermesant, M., Campello, V., Lalande, A., Lekadir, K., Suinesiaputra, A., Camara, O., and Young, A., editors, Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, pages 238–249, Cham. Springer International Publishing.
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11 Ronneberger, O. et al. (2015). U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 9351 of LNCS, pages 234–241. Springer
12 Saifullah, S. et al. (2025). Automatic brain tumor segmentation: advancing u-net with resnet50 encoder for precise medical image analysis. IEEE Access, 13:43473–43489
13 Stirenko, S. et al. (2018). Chest x-ray analysis of tuberculosis by deep learning with segmentation and augmentation. In 2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO), pages 422–428
14 Wang, X. et al. (2020). Automatic segmentation of pneumothorax in chest radiographs based on a two-stage deep learning method. IEEE Transactions on Cognitive and Developmental Systems, 14(1):205–218
15 Yan, W. et al. (2019). The domain shift problem of medical image segmentation and vendor-adaptation by unet-gan. In Shen, D., Liu, T., Peters, T. M., Staib, L. H., Essert, C., Zhou, S., Yap, P.-T., and Khan, A., editors, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, pages 623–631, Cham. Springer International Publishing
16 Yoon, J. S. et al. (2024). Domain generalization for medical image analysis: A review. Proceedings of the IEEE, 112(10):1583–1609
17 Zhang, L. et al. (2020). Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation. IEEE Transactions on Medical Imaging, 39(7):2531–2540