\begin{thebibliography}{10}
\providecommand{\url}[1]{\texttt{#1}}
\providecommand{\urlprefix}{URL }
\providecommand{\doi}[1]{https://doi.org/#1}

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\bibitem{toothfairy3-tmi}
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\bibitem{toothfairy3}
Bolelli, F., Marchesini, K., van Nistelrooij, N., Lumetti, L., Pipoli, V.,
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\bibitem{toothfairy2}
Bolelli, F., Marchesini, K., van Nistelrooij, N., Lumetti, L., Pipoli, V.,
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\bibitem{deeplab}
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\bibitem{xray_leftright}
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\bibitem{mamba2}
Dao, T., Gu, A.: Transformers are {SSM}s: Generalized models and efficient
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\bibitem{mamba}
Gu, A., Dao, T.: Mamba: Linear-time sequence modeling with selective state
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\bibitem{s4}
Gu, A., Goel, K., R\'e, C.: Efficiently modeling long sequences with structured
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\bibitem{resnet}
He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image
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\bibitem{nnunet}
Isensee, F., Jaeger, P.F., Kohl, S.A.A., Petersen, J., Maier-Hein, K.H.:
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\bibitem{nnunet_tf2}
Isensee, F., Kirchhoff, Y., Kraemer, L., Rokuss, M., Ulrich, C., Maier-Hein,
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\bibitem{ssvm}
Islam, M.M., Bertasius, G.: Long movie clip classification with state-space
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\bibitem{clinical_cbct_review}
Jaju, P.P., Jaju, S.P.: Clinical utility of dental cone-beam computed
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\bibitem{cbct_review}
Kaasalainen, T., Ekholm, M., Siiskonen, T., Kortesniemi, M.: Dental cone beam
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\bibitem{liu2021Swin}
Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., Guo, B.: Swin
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\bibitem{toothfairy3-ia}
Lumetti, L., Pipoli, V., Bolelli, F., Ficarra, E., Grana, C.: {Enhancing
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\bibitem{umamba}
Ma, J., Li, F., Wang, B.: U-mamba: Enhancing long-range dependency for
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\bibitem{s4nd}
Nguyen, E., Goel, K., Gu, A., Downs, G.W., Shah, P., Dao, T., Baccus, S.A.,
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\bibitem{cbct_endo}
Patel, S., Durack, C., Abella, F., Shemesh, H., Roig, M., Lemberg, K.: Cone
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\bibitem{sam2}
Ravi, N., Gabeur, V., Hu, Y.T., Hu, R., Ryali, C., Ma, T., Khedr, H.,
  R{\"a}dle, R., Rolland, C., Gustafson, L., Mintun, E., Pan, J., Alwala, K.V.,
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\bibitem{unet}
Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for
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\bibitem{cc3d}
Silversmith, W.: cc3d: Connected components on multilabel 3d \& 2d images (Sep
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\bibitem{swinunetr}
Tang, Y., Yang, D., Li, W., Roth, H.R., Landman, B., Xu, D., Nath, V.,
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  medical image analysis. In: Proc. IEEE Conf. Comput. Vis. Pattern Recog.
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\bibitem{Tang2021SelfSupervisedPO}
Tang, Y., Yang, D., Li, W., Roth, H.R., Landman, B.A., Xu, D., Nath, V.,
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  medical image analysis. In: Proc. IEEE Conf. Comput. Vis. Pattern Recog.
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\bibitem{cbct_use_tyndall2012}
Tyndall, D.A., Price, J.B., Tetradis, S., Ganz, S.D., Hildebolt, C., Scarfe,
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\bibitem{dae}
Valanarasu, J.M.J., Tang, Y., Yang, D., Xu, Z., Zhao, C., Li, W., Patel, V.M.,
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\bibitem{transformer}
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N.,
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\bibitem{sdtooth}
Wang, Y., Ye, F., Chen, Y., Wang, C., Wu, C., Xu, F., Ma, Z., Liu, Y., Zhang,
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\bibitem{setr}
Zheng, S., Lu, J., Zhao, H., Zhu, X., Luo, Z., Wang, Y., Fu, Y., Feng, J.,
  Xiang, T., Torr, P.H., Zhang, L.: Rethinking semantic segmentation from a
  sequence-to-sequence perspective with transformers. In: Proc. IEEE Conf.
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\bibitem{nnformer}
Zhou, H.Y., Guo, J., Zhang, Y., Han, X., Yu, L., Wang, L., Yu, Y.: nnformer:
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\end{thebibliography}
