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Optimizing CT Scan Geometries With and Without Gradients., , , , , , и . CoRR, (2023)Geometric Constraints Enable Self-Supervised Sinogram Inpainting in Sparse-View Tomography., , , , , , , и . CoRR, (2023)Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model., , , , , , , , и . IPMI, том 13939 из Lecture Notes in Computer Science, стр. 183-194. Springer, (2023)Abstract: Robust Multi-contrast MRI Denoising using Trainable Bilateral Filters without Noise-free Targets., , , , , , , , и . Bildverarbeitung für die Medizin, стр. 26. Springer, (2024)Robust Multi-Contrast Mri Denoising Using Trainable Bilateral Filters Without Noise-Free Targets., , , , , , , , , и . ISBI, стр. 1-5. IEEE, (2023)Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT., , , , , , , , , и . CoRR, (2022)On the Influence of Smoothness Constraints in Computed Tomography Motion Compensation., , , , , , , , и . CoRR, (2024)Abstract: Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT., , , , , , , , , и . Bildverarbeitung für die Medizin, стр. 63. Springer, (2023)Abstract: Transient Hemodynamics Prediction using an Efficient Octree-based Deep Learning Model., , , , , , , , и . Bildverarbeitung für die Medizin, стр. 362. Springer, (2024)Abstract: Self-supervised CT Dual Domain Denoising using Low-parameter Models., , , , , , , , , и 2 other автор(ы). Bildverarbeitung für die Medizin, стр. 159. Springer, (2024)