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Towards In-Vivo X-Ray Nanoscopy - Acquisition Parameters vs. Image Quality.

, , , , , and . Bildverarbeitung für die Medizin, page 251-256. Springer Vieweg, (2019)

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Ultra Low-Parameter Denoising: Trainable Bilateral Filter Layers in Computed Tomography., , , , , , , , , and 2 other author(s). CoRR, (2022)Cavity Segmentation in X-ray Microscopy Scans of Mouse Tibiae., , , , , , , , , and 3 other author(s). Bildverarbeitung für die Medizin, page 254-259. Springer, (2023)Towards Mouse Bone X-ray Microscopy Scan Simulation., , , , , , , and . Bildverarbeitung für die Medizin, page 128-133. Springer, (2021)Wafer Direct Bonding: From Advanced Substrate Engineering to Future Applications in Micro/Nanoelectronics., , and . Proc. IEEE, 94 (12): 2060-2106 (2006)Motion Compensation via Epipolar Consistency for In-Vivo X-Ray Microscopy., , , , , , , , , and 2 other author(s). CoRR, (2023)Keynote: 4-D+ nanoSCOPE Project.. Bildverarbeitung für die Medizin, page 2. Springer, (2024)Unsupervised Super Resolution in X-ray Microscopy using a Cycle-consistent Generative Model., , , , , , , , , and 2 other author(s). Bildverarbeitung für die Medizin, page 76-81. Springer, (2023)Monte Carlo Dose Simulation for In-Vivo X-Ray Nanoscopy., , , , , , , , , and 2 other author(s). Bildverarbeitung für die Medizin, page 107-112. Springer, (2022)Learning with known operators reduces maximum error bounds., , , , , , , , , and . Nat. Mach. Intell., 1 (8): 373-380 (2019)Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation., , , , , , , , , and 5 other author(s). CoRR, (2020)