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Abstract: Self-supervised CT Dual Domain Denoising using Low-parameter Models.

, , , , , , , , , , , and . Bildverarbeitung für die Medizin, page 159. Springer, (2024)

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