Fetching the paper…
Reading the bibliography…
Volumetric medical image segmentation is pivotal in enhancing disease diagnosis, treatment planning, and advancing medical research.
Jacobs, R.A., Jordan, M.I., Nowlan, S.J., Hinton, G.E.: Adaptive mixtures of local experts. Neural computation 3
1991
Earlier work this paper cites.
2010
Earlier work this paper cites.
Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18. pp. 234–241. Springer (2015)
2015
Earlier work this paper cites.
2017
Earlier work this paper cites.
2020
Earlier work this paper cites.
2021
Earlier work this paper cites.
Isensee, F., Jaeger, P.F., Kohl, S.A., Petersen, J., Maier-Hein, K.H.: nnu-net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods 18
2021
Earlier work this paper cites.
Ma, J., Zhang, Y., Gu, S., Zhu, C., Ge, C., Zhang, Y., An, X., Wang, C., Wang, Q., Liu, X., Cao, S., Zhang, Q., Liu, S., Wang, Y., Li, Y., He, J., Yang, X.: Abdomenct-1k: Is abdominal organ segmentation a solved problem? IEEE Transactions on Pattern Analysis and Machine Intelligence 44
2021
Cited alongside, same era.
Antonelli, M., Reinke, A., Bakas, S., Farahani, K., Kopp-Schneider, A., Landman, B.A., Litjens, G., Menze, B., Ronneberger, O., Summers, R.M., et al.: The medical segmentation decathlon. Nature communications 13
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Fedus, W., Zoph, B., Shazeer, N.: Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity. The Journal of Machine Learning Research 23
2022
Huang, Z., Wang, H., Deng, Z., Ye, J., Su, Y., Sun, H., He, J., Gu, Y., Gu, L., Zhang, S., Qiao, Y.: Stu-net: Scalable and transferable medical image segmentation models empowered by large-scale supervised pre-training (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
Wang, H., Guo, S., Ye, J., Deng, Z., Cheng, J., Li, T., Chen, J., Su, Y., Huang, Z., Shen, Y., Fu, B., Zhang, S., He, J., Qiao, Y.: Sam-med3d (2023)
2023
Later among the works it cites.
Dou, S., Zhou, E., Liu, Y., Gao, S., Zhao, J., Shen, W., Zhou, Y., Xi, Z., Wang, X., Fan, X., Pu, S., Zhu, J., Zheng, R., Gui, T., Zhang, Q., Huang, X.: Loramoe: Alleviate world knowledge forgetting in large language models via moe-style plugin (2024)
2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Ji, Y., Bai, H., GE, C., Yang, J., Zhu, Y., Zhang, R., Li, Z., Zhang, L., Ma, W., Wan, X., Luo, P.: Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation. In: Advances in Neural Information Processing Systems. vol. 35, pp. 36722–36732 (2022)
2022
Cited alongside, same era.
Buser, M.A., van der Steeg, A.F., Simons, D.C., Wijnen, M.H., Littooij, A.S., ter Brugge, A.H., Vos, I.N., van der Velden, B.H.: Surgical planning in pediatric neuroblastoma. In: International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2023. Zenodo (2023), https://doi.org/10.5281/zenodo.7848306
2023
Cited alongside, same era.
Cheng, J., Ye, J., Deng, Z., Chen, J., Li, T., Wang, H., Su, Y., Huang, Z., Chen, J., Jiang, L., Sun, H., He, J., Zhang, S., Zhu, M., Qiao, Y.: Sam-med2d (2023)
2023
Cited alongside, same era.
Du, Y., Bai, F., Huang, T., Zhao, B.: Segvol: Universal and interactive volumetric medical image segmentation (2024)
2024
Closest in time.
2024
Closest in time.
Ma, J., He, Y., Li, F., Han, L., You, C., Wang, B.: Segment anything in medical images. Nature Communications 15
2024
Closest in time.