most citedDiffusion Models for Implicit Image Segmentation Ensembles

71 citations · 79 across the 5 of their papers we have counts for

collaborators

5 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.IV20233 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

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…

cs.CV202171 cited

Diffusion Models for Implicit Image Segmentation Ensembles

Julia Wolleb, Robin Sandkühler, Florentin Bieder +2

Diffusion models have shown impressive performance for generative modelling of images. In this paper, we present a novel semantic segmentation method based on diffusion models. By…

cs.CV20215 cited

Comparison of Methods Generalizing Max- and Average-Pooling

Florentin Bieder, Robin Sandkühler, Philippe C. Cattin

Max- and average-pooling are the most popular pooling methods for downsampling in convolutional neural networks. In this paper, we compare different pooling methods that generalize…