MSMV-UNet: A 2.5D Stroke Lesion Segmentation Method Based on Multi-slice Feature Fusion
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-53311-2_5
Reference21 articles.
1. Basak, H., Hussain, R., Rana, A.: DFENet: a novel dimension fusion edge guided network for brain MRI segmentation. SN Comput. Sci. 2, 1–11 (2021)
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3. Dolz, J., Ben Ayed, I., Desrosiers, C.: Dense multi-path U-Net for ischemic stroke lesion segmentation in multiple image modalities. In: Crimi, A., Bakas, S., Kuijf, H., Keyvan, F., Reyes, M., van Walsum, T. (eds.) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, 16 September 2018, Revised Selected Papers, Part I 4. LNCS, vol. 11383, pp. 271–282. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-11723-8_27
4. Hui, H., Zhang, X., Li, F., Mei, X., Guo, Y.: A partitioning-stacking prediction fusion network based on an improved attention U-Net for stroke lesion segmentation. IEEE Access 8, 47419–47432 (2020)
5. Kim, J., et al.: Global stroke statistics 2019. Int. J. Stroke 15(8), 819–838 (2020)
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