activity
20172023
most citedDiffusion Models for Implicit Image Segmentation Ensembles

71 citations · 257 across the 23 of their papers we have counts for

collaborators

24 papers

eess.IV2023

GAMER-MRIL identifies Disability-Related Brain Changes in Multiple Sclerosis

Po-Jui Lu, Benjamin Odry, Muhamed Barakovic +9

Objective: Identifying disability-related brain changes is important for multiple sclerosis (MS) patients. Currently, there is no clear understanding about which pathological featu…

eess.IV2023★ 3 cited

Diffusion Models for Contrast Harmonization of Magnetic Resonance Images

Alicia Durrer, Julia Wolleb, Florentin Bieder +6

Magnetic resonance (MR) images from multiple sources often show differences in image contrast related to acquisition settings or the used scanner type. For long-term studies, longi…

cs.CV2023★ 8 cited

Memory-Efficient 3D Denoising Diffusion Models for Medical Image Processing

Florentin Bieder, Julia Wolleb, Alicia Durrer +2

Denoising diffusion models have recently achieved state-of-the-art performance in many image-generation tasks. They do, however, require a large amount of computational resources.…

eess.IV2023★ 19 cited

Point Cloud Diffusion Models for Automatic Implant Generation

Paul Friedrich, Julia Wolleb, Florentin Bieder +2

Advances in 3D printing of biocompatible materials make patient-specific implants increasingly popular. The design of these implants is, however, still a tedious and largely manual…

eess.IV2023

Improved distinct bone segmentation in upper-body CT through multi-resolution networks

Eva Schnider, Julia Wolleb, Antal Huck +4

Purpose: Automated distinct bone segmentation from CT scans is widely used in planning and navigation workflows. U-Net variants are known to provide excellent results in supervised…

cs.CV2023

Position Regression for Unsupervised Anomaly Detection

Florentin Bieder, Julia Wolleb, Robin Sandkühler +1

In recent years, anomaly detection has become an essential field in medical image analysis. Most current anomaly detection methods for medical images are based on image reconstruct…