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From the 1 of 8 linked papers with an AI index.

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8 papers

cs.CV2026

GB-SVFBP: Gaussian-Based Shift-Variant FBP neural network

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

The paper introduces a Gaussian-based shift-variant filtered backprojection neural network that efficiently reconstructs cone-beam CT images from non-circular trajectories with far…

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…

cs.CV2026

Soft Tuy-Completeness for Robust Projection Selection in Cone-Beam CT

Linda-Sophie Schneider, Andreas Maier

This work introduces a continuous soft near-orthogonality score and a resolution-aware saturated coverage objective for projection selection in region-of-interest focused cone-beam…

cs.CV2026

ICDAR 2026 Competition on Writer Identification and Pen Classification from Hand-Drawn Circles

Thomas Gorges, Janne van der Loop, Lukas Hüttner +4

This paper presents CircleID, a large-scale ICDAR 2026 competition on writer identification and pen classification from scanned hand-drawn circles. The primary objective is to inve…

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…

cs.LG2025

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…