71 citations · 162 across the 11 of their papers we have counts for
12 papers
Conditional Graph Neural Network for Predicting Soft Tissue Deformation and Forces
Madina Kojanazarova, Florentin Bieder, Robin Sandkühler +1
Soft tissue simulation in virtual environments is becoming increasingly important for medical applications. However, the high deformability of soft tissue poses significant challen…
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…
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…
The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models
Julia Wolleb, Robin Sandkühler, Florentin Bieder +1
Recently, diffusion models were applied to a wide range of image analysis tasks. We build on a method for image-to-image translation using denoising diffusion implicit models and i…
Diffusion Models for Medical Anomaly Detection
Julia Wolleb, Florentin Bieder, Robin Sandkühler +1
In medical applications, weakly supervised anomaly detection methods are of great interest, as only image-level annotations are required for training. Current anomaly detection met…
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…
Learn to Ignore: Domain Adaptation for Multi-Site MRI Analysis
Julia Wolleb, Robin Sandkühler, Florentin Bieder +7
The limited availability of large image datasets, mainly due to data privacy and differences in acquisition protocols or hardware, is a significant issue in the development of accu…
MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets
Orso Pusterla, Rahel Heule, Francesco Santini +8
Purpose: To introduce a widely applicable workflow for pulmonary lobe segmentation of MR images using a recurrent neural network (RNN) trained with chest computed tomography (CT) d…
DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision
Julia Wolleb, Robin Sandkühler, Philippe C. Cattin
Anomaly detection and localization in medical images is a challenging task, especially when the anomaly exhibits a change of existing structures, e.g., brain atrophy or changes in…
Accelerated Motion-Aware MR Imaging via Motion Prediction from K-Space Center
Christoph Jud, Damien Nguyen, Alina Giger +6
Motion has been a challenge for magnetic resonance (MR) imaging ever since the MR has been invented. Especially in volumetric imaging of thoracic and abdominal organs, motion-aware…
Recurrent Registration Neural Networks for Deformable Image Registration
Robin Sandkühler, Simon Andermatt, Grzegorz Bauman +3
Parametric spatial transformation models have been successfully applied to image registration tasks. In such models, the transformation of interest is parameterized by a fixed set…
AirLab: Autograd Image Registration Laboratory
Robin Sandkühler, Christoph Jud, Simon Andermatt +1
Medical image registration is an active research topic and forms a basis for many medical image analysis tasks. Although image registration is a rather general concept specialized…