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20242026
most citedA gradient-based approach to fast and accurate head motion compensation in cone-beam CT

6 citations · 13 across the 19 of their papers we have counts for

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Showing 2024 · cs.CVShow all

7 papers · 2 filters

cs.CV2024

DRACO: Differentiable Reconstruction for Arbitrary CBCT Orbits

Chengze Ye, Linda-Sophie Schneider, Yipeng Sun +3

This paper introduces a novel method for reconstructing cone beam computed tomography (CBCT) images for arbitrary orbits using a differentiable shift-variant filtered backprojectio…

cs.CV2024★ 1 cited

Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals

Susu Sun, Stefano Woerner, Andreas Maier +2

Interpretability is crucial for machine learning algorithms in high-stakes medical applications. However, high-performing neural networks typically cannot explain their predictions…

cs.CV2024★ 1 cited

Application of Gated Recurrent Units for CT Trajectory Optimization

Yuedong Yuan, Linda-Sophie Schneider, Andreas Maier

Recent advances in computed tomography (CT) imaging, especially with dual-robot systems, have introduced new challenges for scan trajectory optimization. This paper presents a nove…

cs.CV2024

Differentiable Score-Based Likelihoods: Learning CT Motion Compensation From Clean Images

Mareike Thies, Noah Maul, Siyuan Mei +8

Motion artifacts can compromise the diagnostic value of computed tomography (CT) images. Motion correction approaches require a per-scan estimation of patient-specific motion patte…

cs.CV2024

BigReg: An Efficient Registration Pipeline for High-Resolution X-Ray and Light-Sheet Fluorescence Microscopy

Siyuan Mei, Fuxin Fan, Mareike Thies +9

Recently, X-ray microscopy (XRM) and light-sheet fluorescence microscopy (LSFM) have emerged as pivotal tools in preclinical research, particularly for studying bone remodeling dis…

cs.CV2024★ 2 cited

Deep Learning Computed Tomography based on the Defrise and Clack Algorithm

Chengze Ye, Linda-Sophie Schneider, Yipeng Sun +1

This study presents a novel approach for reconstructing cone beam computed tomography (CBCT) for specific orbits using known operator learning. Unlike traditional methods, this tec…

cs.CV2024

A 2D Sinogram-Based Approach to Defect Localization in Computed Tomography

Yuzhong Zhou, Linda-Sophie Schneider, Fuxin Fan +1

The rise of deep learning has introduced a transformative era in the field of image processing, particularly in the context of computed tomography. Deep learning has made a signifi…