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Focus on Content not Noise: Improving Image Generation for Nuclei Segmentation by Suppressing Steganography in CycleGAN.

, , , , , , , and . ICCV (Workshops), page 3858-3866. IEEE, (2023)

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Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimization for Multi-Modal Cardiac Image Segmentation., , , , and . IEEE Trans. Medical Imaging, 40 (7): 1838-1851 (2021)Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series., , , , , , , , and . CoRR, (2024)Abstract: Gradient-based Geometry Learning for Fan-beam CT Reconstruction., , , , , , , , , and 3 other author(s). Bildverarbeitung für die Medizin, page 204. Springer, (2024)EAGLE: An Edge-Aware Gradient Localization Enhanced Loss for CT Image Reconstruction., , , , , , , and . CoRR, (2024)Spatio-Temporal Multi-Task Learning for Cardiac MRI Left Ventricle Quantification., , , and . IEEE J. Biomed. Health Informatics, 25 (7): 2698-2709 (2021)Noise2Contrast: Multi-Contrast Fusion Enables Self-Supervised Tomographic Image Denoising., , , , , , , , , and 3 other author(s). CoRR, (2022)On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting., , , , , , , , , and 2 other author(s). CoRR, (2022)Ultra Low-Parameter Denoising: Trainable Bilateral Filter Layers in Computed Tomography., , , , , , , , , and 2 other author(s). 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: Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT., , , , , , , , , and . Bildverarbeitung für die Medizin, page 63. Springer, (2023)