6 citations · 13 across the 19 of their papers we have counts for
5 papers · 1 filter
An update to PYRO-NN: A Python Library for Differentiable CT Operators
Linda-Sophie Schneider, Yipeng Sun, Chengze Ye +2
Deep learning has brought significant advancements to X-ray Computed Tomography (CT) reconstruction, offering solutions to challenges arising from modern imaging technologies. Thes…
FIND-Net -- Fourier-Integrated Network with Dictionary Kernels for Metal Artifact Reduction
Farid Tasharofi, Fuxin Fan, Melika Qahqaie +2
Metal artifacts, caused by high-density metallic implants in computed tomography (CT) imaging, severely degrade image quality, complicating diagnosis and treatment planning. While…
Learning Wavelet-Sparse FDK for 3D Cone-Beam CT Reconstruction
Yipeng Sun, Linda-Sophie Schneider, Chengze Ye +4
Cone-Beam Computed Tomography (CBCT) is essential in medical imaging, and the Feldkamp-Davis-Kress (FDK) algorithm is a popular choice for reconstruction due to its efficiency. How…
Filter2Noise: A Framework for Interpretable and Zero-Shot Low-Dose CT Image Denoising
Yipeng Sun, Linda-Sophie Schneider, Siyuan Mei +8
Noise in low-dose computed tomography (LDCT) can obscure important diagnostic details. While deep learning offers powerful denoising, supervised methods require impractical paired…
Compressibility Analysis for the differentiable shift-variant Filtered Backprojection Model
Chengze Ye, Linda-Sophie Schneider, Yipeng Sun +2
The differentiable shift-variant filtered backprojection (FBP) model enables the reconstruction of cone-beam computed tomography (CBCT) data for any non-circular trajectories. This…