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Intelligent medical image segmentation methods are rapidly evolving and being increasingly applied, yet they face the challenge of domain transfer, where algorithm performance degrades due to different data distributions between source and target domains.
Sorensen, T., “A method of establishing groups of equal amplitude in plant sociology based on similarity of species content and its application to analyses of the vegetation on danish commons,” Biologiske skrifter
1948
Earlier work this paper cites.
Ambellan, F., Tack, A., Ehlke, M., and Zachow, S., “Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the osteoarthritis initiative,” Medical image analysis
2019
Earlier work this paper cites.
2023
Earlier work this paper cites.
Cheng, J., Ye, J., Deng, Z., Chen, J., Li, T., Wang, H., Su, Y., Huang, Z., Chen, J., Sun, L. J. H., He, J., Zhang, S., Zhu, M., and Qiao, Y., “Sam-med2d,” (2023)
2023
Cited alongside, same era.
Mazurowski, M. A., Dong, H., Gu, H., Yang, J., Konz, N., and Zhang, Y., “Segment anything model for medical image analysis: an experimental study,” Medical Image Analysis
2023
Cited alongside, same era.
Wu, J., Ji, W., Liu, Y., Fu, H., Xu, M., Xu, Y., and Jin, Y., “Medical sam adapter: Adapting segment anything model for medical image segmentation,” (2023)
2023
Cited alongside, same era.
Ryali, C., Hu, Y.-T., Bolya, D., Wei, C., Fan, H., Huang, P.-Y., Aggarwal, V., Chowdhury, A., Poursaeed, O., Hoffman, J., Malik, J., Li, Y., and Feichtenhofer, C., “Hiera: A hierarchical vision transformer without the bells-and-whistles,” ICML
2023
Later among the works it cites.
Ma, J., He, Y., Li, F., Han, L., You, C., and Wang, B., “Segment anything in medical images,” Nature Communications
2024
Closest in time.
2024
Closest in time.
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