22 citations · 34 across the 39 of their papers we have counts for
8 papers · 1 filter
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…
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…
A Self-supervised Multimodal Deep Learning Approach to Differentiate Post-radiotherapy Progression from Pseudoprogression in Glioblastoma
Ahmed Gomaa, Yixing Huang, Pluvio Stephan +19
Accurate differentiation of pseudoprogression (PsP) from True Progression (TP) following radiotherapy (RT) in glioblastoma (GBM) patients is crucial for optimal treatment planning.…
EAGLE: An Edge-Aware Gradient Localization Enhanced Loss for CT Image Reconstruction
Yipeng Sun, Yixing Huang, Linda-Sophie Schneider +5
Computed Tomography (CT) image reconstruction is crucial for accurate diagnosis and deep learning approaches have demonstrated significant potential in improving reconstruction qua…
Attention-Guided Erasing: A Novel Augmentation Method for Enhancing Downstream Breast Density Classification
Adarsh Bhandary Panambur, Hui Yu, Sheethal Bhat +3
The assessment of breast density is crucial in the context of breast cancer screening, especially in populations with a higher percentage of dense breast tissues. This study introd…
Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series
Yipeng Sun, Linda-Sophie Schneider, Fuxin Fan +6
In this study, we introduce a Fourier series-based trainable filter for computed tomography (CT) reconstruction within the filtered backprojection (FBP) framework. This method over…
Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach
Siming Bayer, Xia Zhong, Weilin Fu +2
Comparison of microvascular circulation on fundoscopic images is a non-invasive clinical indication for the diagnosis and monitoring of diseases, such as diabetes and hypertensions…