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From the 1 of 14 linked papers with an AI index.

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20242026
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eess.IV2026

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…

eess.IV2026

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…

eess.IV2025

seg2med: a bridge from artificial anatomy to multimodal medical images

Zeyu Yang, Zhilin Chen, Yipeng Sun +5

We present seg2med, a modular framework for anatomy-driven multimodal medical image synthesis. The system integrates three components to enable high-fidelity, cross-modality genera…

eess.IV2025

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…

eess.IV2024

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…