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English Information

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Authors
# Name
1 jefferson dos Anjos(jefferson.ti@hotmail.com.br)
2 Felipe Henriques(felipe.henriques@cefet-rj.br)
3 Nordeval Araújo(nordevalaraujo@gmail.com)
4 Jorge Luiz Henriques Junior(jorgehenriquesjr@gmail.com)
5 José Hermógenes Suassuna(rocco@uerj.br)
6 Amaro de Lima(amaro.lima@cefet-rj.br)
7 Gabriel Araújo()

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Reference
# Reference
1 Chavhan, G. B., Parra, D. A., Oudjhane, K., et al. (2008). Renal pyramid echogenicity in ureteropelvic junction obstruction: correlation between altered echogenicity and differential renal function. Pediatric Radiology, 38(10):1063-1069.
2 Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., and Adam, H. (2018). Encoder-decoder with atrous separable convolution for semantic image segmentation. European Conference on Computer Vision (ECCV), pages 801-818.
3 Constantino, K., Cruz, V. A. L., Zucheratto, O. M. M., Franca, C., Carvalho, M., Silva, T. H. P., Laender, A. H. F., and Goncalves, M. A. (2022). Segmentacao e classificacao semantica de trechos de diarios oficiais usando aprendizado ativo. In Anais do XXXVII Simposio Brasileiro de Banco de Dados (SBBD), pages 304-316. Sociedade Brasileira de Computacao.
4 Dice, L. R. (1945). Measures of the amount of ecologic association between species. Ecology, 26(3):297-302.
5 Jaccard, P. (1901). Etude comparative de la distribution florale dans une portion des alpes et des jura. Bulletin de la Societe Vaudoise des Sciences Naturelles, 37:547-579.
6 Lee, D.-H. (2013). Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks. In Workshop on Challenges in Representation Learning, ICML, volume 3.
7 Lima, D. M., Moreno, R. A., Pires, F. A., and Gutierrez, M. A. (2021). Uma proposta de data lake para pesquisa em saude a partir de data pools multicentricos interoperaveis. In Anais do XXXVI Simposio Brasileiro de Banco de Dados (SBBD), pages 367-372. Sociedade Brasileira de Computacao.
8 Manley, J. A. and O'Neill, W. C. (2001). How echogenic is echogenic? quantitative acoustics of the renal cortex. American Journal of Kidney Diseases, 37(4):706-711.
9 Ronneberger, O., Fischer, P., and Brox, T. (2015). U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention (MICCAI), pages 234-241.
10 Singla, R., Ringstrom, C., Hu, G., Lessoway, V., Reid, J., Nguan, C., and Rohling, R. (2023). The open kidney ultrasound data set. In Simplifying Medical Ultrasound, volume 14337 of Lecture Notes in Computer Science, pages 155-164. Springer Nature Switzerland.
11 Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J. M., and Luo, P. (2021). Segformer: Simple and efficient design for semantic segmentation with transformers. Advances in Neural Information Processing Systems, 34:12077-12090.
12 Zuiderveld, K. (1994). Contrast limited adaptive histogram equalization. In Heckbert, P. S., editor, Graphics Gems IV, pages 474-485. Academic Press.