A class-aware multi-stage UDA framework for prostate zonal segmentation
Author:
Funder
National Natural Science Foundation of China
Scientific Research Seed Fund of Peking University First Hospital
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-18095-7.pdf
Reference44 articles.
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2. Antonelli M, Reinke A, Bakas S, Farahani K, Kopp-Schneider A, Landman BA, Litjens G, Menze B, Ronneberger O, Summers RM et al (2022) The medical segmentation decathlon. Nat Commun 13(1):1–13
3. Mårtensson G, Ferreira D, Granberg T, Cavallin L, Oppedal K, Padovani A, Rektorova I, Bonanni L, Pardini M, Kramberger MG et al (2020) The reliability of a deep learning model in clinical out-of-distribution mri data: a multicohort study. Med Image Anal 66:101714
4. Gibson E, Hu Y, Ghavami N, Ahmed HU, Moore C, Emberton M, Huisman HJ, Barratt DC (2018) Inter-site variability in prostate segmentation accuracy using deep learning. In: International conference on medical image computing and computer-assisted intervention, pp 506–514. Springer
5. Guo X, Yang C, Li B, Yuan Y Metacorrection: domain-aware meta loss correction for unsupervised domain adaptation in semantic segmentation. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 3927–3936 (2021)
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