Evaluation of Transfer Learning with a U-Net Architectures for Kidney Segmentation

Author:

Matos Caio Eduardo FalcãoORCID,do Vale João Guilherme AraújoORCID,Ferreira Marcos MeloORCID,Júnior Geraldo BrazORCID,de Almeida João Dallyson SousaORCID

Publisher

Springer Nature Switzerland

Reference33 articles.

1. ACS: American cancer society - key statistics about kidney cancer (2022). https://www.cancer.org/cancer/kidney-cancer/about/key-statistics.html

2. ACS: American cancer society - survival rates for kidney cancer (2022). https://www.cancer.org/cancer/kidney-cancer/detection-diagnosis-staging/survival-rates.html

3. Arbelle, A., Raviv, T.R.: Microscopy cell segmentation via convolutional LSTM networks. In: 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 1008–1012. IEEE, Hilton Molino Stucky, Venice (2019)

4. Azad, R., Asadi-Aghbolaghi, M., Fathy, M., Escalera, S.: Bi-directional ConvLSTM U-net with densley connected convolutions. In: Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops. IEEE, Seoul (2019)

5. Causey, J., et al.: An ensemble of U-net models for kidney tumor segmentation with CT images. IEEE/ACM Trans. Comput. Biol. Bioinf. 19(3), 1387–1392 (2021)

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