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Noah Maul

Pattern Recognition Lab, FAU Erlangen-Nürnberg, Germany, Siemens Healthcare GmbH, Forchheim, Germany

On the Influence of Smoothness Constraints in Computed Tomography Motion Compensation

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May 29, 2024
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Differentiable Score-Based Likelihoods: Learning CT Motion Compensation From Clean Images

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Apr 23, 2024
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Physics-Informed Learning for Time-Resolved Angiographic Contrast Agent Concentration Reconstruction

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Mar 04, 2024
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A gradient-based approach to fast and accurate head motion compensation in cone-beam CT

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Jan 17, 2024
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Geometric Constraints Enable Self-Supervised Sinogram Inpainting in Sparse-View Tomography

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Feb 13, 2023
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Optimizing CT Scan Geometries With and Without Gradients

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Feb 13, 2023
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Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model

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Feb 13, 2023
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Noise2Contrast: Multi-Contrast Fusion Enables Self-Supervised Tomographic Image Denoising

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Dec 09, 2022
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Gradient-Based Geometry Learning for Fan-Beam CT Reconstruction

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Dec 05, 2022
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On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting

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Nov 03, 2022
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