Learning-based Patch-wise Metal Segmentation with Consistency Check
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Publisher
Springer Fachmedien Wiesbaden
Link
http://link.springer.com/content/pdf/10.1007/978-3-658-33198-6_4
Reference8 articles.
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2. Meyer E, Raupach R, Lell M, et al. Normalized metal artifact reduction (NMAR) in computed tomography. Med Phys. 2010;37(10):5482–5493.
3. Meyer E, Raupach R, Lell M, et al. Frequency split metal artifact reduction (FSMAR) in computed tomography. Med Phys. 2012;39(4):1904–1916.
4. Ronneberger O, Fischer P, Brox T; Springer. U-net: Convolutional networks for biomedical image segmentation. Proc MICCAI. 2015; p. 234–241.
5. Yu L, Zhang Z, Li X, et al. Deep sinogram completion with image prior for metal artifact reduction in CT images. IEEE Trans Med Imaging. 2020; p. 1–1.
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