Diffusion Kinetic Model for Breast Cancer Segmentation in Incomplete DCE-MRI
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-43901-8_10
Reference21 articles.
1. Fan, M., Xia, P., Clarke, R., Wang, Y., Li, L.: Radiogenomic signatures reveal multiscale intratumour heterogeneity associated with biological functions and survival in breast cancer. Nat. Commun. 11(1), 4861 (2020)
2. Vidal, J., Vilanova, J.C., Martí, R., et al.: A U-net ensemble for breast lesion segmentation in DCE MRI. Comput. Biol. Med. 140, 105093 (2022)
3. Qiao, M., et al.: Three-dimensional breast tumor segmentation on DCE-MRI with a multilabel attention-guided joint-phase-learning network. Comput. Med. Imaging Graph. 90, 101909 (2021)
4. Nalepa, J., et al.: Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors. Artif. Intell. Med. 102, 101769 (2020)
5. Lv, T., et al.: A hybrid hemodynamic knowledge-powered and feature reconstruction-guided scheme for breast cancer segmentation based on dce-mri. Med. Image Anal. 82, 102572 (2022)
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