2 citations · 2 across the 10 of their papers we have counts for
10 papers
GB-SVFBP: Gaussian-Based Shift-Variant FBP neural network
Chengze Ye, Linda-Sophie Schneider, Yipeng Sun +1
This paper proposes a Gaussian-Based Shift-Variant filtered backprojection (FBP) neural network, which is designed for the efficient reconstruction of non-circular trajectory cone…
Robustness and Stability Analysis of Differentiable Shift-Variant FBP for Cone-Beam CT under Challenging Acquisition Settings
Chengze Ye, Linda-Sophie Schneider, Yipeng Sun +5
The differentiable shift-variant filtered backprojection (SV-FBP) framework enables data-driven estimation of redundancy weights for cone-beam CT reconstruction under general sourc…
WING: A Window-Prior-Based Generative Network with Gated Inception for Cross-Modality CT Synthesis
Siyuan Mei, Yan Xia, Yipeng Sun +7
Generating CT volumes from MRI and CBCT can improve treatment planning in adaptive radiotherapy while avoiding additional radiation exposure. However, direct regression of CT inten…
Speech-Guided Multimodal Learning for Vocal Tract Segmentation in Real-Time MRI
Daiqi Liu, Lukas Mulzer, Md Hasan +11
Segmenting vocal tract articulators in real-time MRI (rtMRI) is a challenging dynamic image segmentation problem characterized by low contrast, rapid motion, and limited spatial re…
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…
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…
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…
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…