Noah Maul

Orcid: 0000-0003-1161-1299

According to our database1, Noah Maul authored at least 17 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Physics-Informed Learning for Time-Resolved Angiographic Contrast Agent Concentration Reconstruction.
CoRR, 2024

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

Abstract: Self-supervised CT Dual Domain Denoising using Low-parameter Models.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

Abstract: Gradient-based Geometry Learning for Fan-beam CT Reconstruction.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

Abstract: Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

Abstract: Transient Hemodynamics Prediction using an Efficient Octree-based Deep Learning Model.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023
Continuous Non-Invasive Blood Pressure Measurement Using 60 GHz-Radar - A Feasibility Study.
Sensors, 2023

Geometric Constraints Enable Self-Supervised Sinogram Inpainting in Sparse-View Tomography.
CoRR, 2023

Optimizing CT Scan Geometries With and Without Gradients.
CoRR, 2023

Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

On the Benefit of Dual-Domain Denoising in a Self-Supervised Low-Dose CT Setting.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Robust Multi-Contrast Mri Denoising Using Trainable Bilateral Filters Without Noise-Free Targets.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Noise2Contrast: Multi-contrast Fusion Enables Self-supervised Tomographic Image Denoising.
Proceedings of the Information Processing in Medical Imaging, 2023

Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model.
Proceedings of the Information Processing in Medical Imaging, 2023

Abstract: Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022
Gradient-Based Geometry Learning for Fan-Beam CT Reconstruction.
CoRR, 2022

Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT.
CoRR, 2022


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