83 citations · 107 across the 7 of their papers we have counts for
8 papers
Domain-adaptive Zero-Shot Image Enhancement via Locality-Constrained Diffusion Guidance
Theresa Neubauer, Dimitrios Lenis, Astrid Berg +7
Denoising Diffusion Probabilistic Models have shown remarkable performance in unconditional image generation. In order to generate images with desired semantics, recent works have…
PARMESAN: Parameter-Free Memory Search and Transduction for Dense Prediction Tasks
Philip Matthias Winter, Maria Wimmer, David Major +7
This work addresses flexibility in deep learning by means of transductive reasoning. For adaptation to new data and tasks, e.g., in continual learning, existing methods typically i…
Anomaly Detection using Generative Models and Sum-Product Networks in Mammography Scans
Marc Dietrichstein, David Major, Martin Trapp +6
Unsupervised anomaly detection models which are trained solely by healthy data, have gained importance in the recent years, as the annotation of medical data is a tedious task. Aut…
Soft Tissue Sarcoma Co-Segmentation in Combined MRI and PET/CT Data
Theresa Neubauer, Maria Wimmer, Astrid Berg +5
Tumor segmentation in multimodal medical images has seen a growing trend towards deep learning based methods. Typically, studies dealing with this topic fuse multimodal image data…
Domain aware medical image classifier interpretation by counterfactual impact analysis
Dimitrios Lenis, David Major, Maria Wimmer +3
The success of machine learning methods for computer vision tasks has driven a surge in computer assisted prediction for medicine and biology. Based on a data-driven relationship b…
Interpreting Medical Image Classifiers by Optimization Based Counterfactual Impact Analysis
David Major, Dimitrios Lenis, Maria Wimmer +3
Clinical applicability of automated decision support systems depends on a robust, well-understood classification interpretation. Artificial neural networks while achieving class-le…
Deep Sequential Segmentation of Organs in Volumetric Medical Scans
Alexey Novikov, David Major, Maria Wimmer +2
Segmentation in 3D scans is playing an increasingly important role in current clinical practice supporting diagnosis, tissue quantification, or treatment planning. The current 3D a…
Hatching for 3D prints: line-based halftoning for dual extrusion fused deposition modeling
Tim Kuipers, Willemijn Elkhuizen, Jouke Verlinden +1
This work presents a halftoning technique to manufacture 3D objects with the appearance of continuous grayscale imagery for Fused Deposition Modeling (FDM) printers. While droplet-…