8 citations · 11 across the 7 of their papers we have counts for
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MedDiME: Efficient Latent Diffusion with Adaptive Masking for Medical Counterfactual Generation
Yan Zeng, Changlu Guo, Anders Nymark Christensen +2
Medical counterfactual generation modifies images to change model predictions for interpretability. However, existing diffusion-based approaches are often prohibitively slow and me…
FiRe: Fixed-Noise Refinement for Visual Counterfactual Explanations
Yan Zeng, Changlu Guo, Oskar Kristoffersen +3
Visual counterfactual explanations aim to change classifier decisions through realistic and localized edits while preserving decision-irrelevant content. Existing DDPM-based method…
MaskDiME: Adaptive Masked Diffusion for Precise and Efficient Visual Counterfactual Explanations
Changlu Guo, Anders Nymark Christensen, Anders Bjorholm Dahl +1
Visual counterfactual explanations aim to reveal the minimal semantic modifications that can alter a model's prediction, providing causal and interpretable insights into deep neura…
SA-UNetv2: Rethinking Spatial Attention U-Net for Retinal Vessel Segmentation
Changlu Guo, Anders Nymark Christensen, Anders Bjorholm Dahl +2
Retinal vessel segmentation is essential for early diagnosis of diseases such as diabetic retinopathy, hypertension, and neurodegenerative disorders. Although SA-UNet introduces sp…
Fast Sphericity and Roundness approximation in 2D and 3D using Local Thickness
Pawel Tomasz Pieta, Peter Winkel Rasumssen, Anders Bjorholm Dahl +1
Sphericity and roundness are fundamental measures used for assessing object uniformity in 2D and 3D images. However, using their strict definition makes computation costly. As both…
Materialist: Physically Based Editing Using Single-Image Inverse Rendering
Lezhong Wang, Duc Minh Tran, Ruiqi Cui +5
Achieving physically consistent image editing remains a significant challenge in computer vision. Existing image editing methods typically rely on neural networks, which struggle t…
MozzaVID: Mozzarella Volumetric Image Dataset
Pawel Tomasz Pieta, Peter Winkel Rasmussen, Anders Bjorholm Dahl +4
Influenced by the complexity of volumetric imaging, there is a shortage of established datasets useful for benchmarking volumetric deep-learning models. As a consequence, new and e…
Feature-Centered First Order Structure Tensor Scale-Space in 2D and 3D
Pawel Tomasz Pieta, Anders Bjorholm Dahl, Jeppe Revall Frisvad +2
The structure tensor method is often used for 2D and 3D analysis of imaged structures, but its results are in many cases very dependent on the user's choice of method parameters. W…