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20212024
most citedThe RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification

89 citations · 184 across the 19 of their papers we have counts for

collaborators

19 papers

eess.IV20241 cited

MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI

Malek Ben Alaya, Daniel M. Lang, Benedikt Wiestler +2

Denoising diffusion probabilistic models enable high-fidelity image synthesis and editing. In biomedicine, these models facilitate counterfactual image editing, producing pairs of…

cs.HC2024

A Framework for Multimodal Medical Image Interaction

Laura Schütz, Sasan Matinfar, Gideon Schafroth +6

Medical doctors rely on images of the human anatomy, such as magnetic resonance imaging (MRI), to localize regions of interest in the patient during diagnosis and treatment. Despit…

eess.IV2024

Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders

Mehmet Yigit Avci, Emily Chan, Veronika Zimmer +4

With the increasing incidence of neurodegenerative diseases such as Alzheimer's Disease (AD), there is a need for further research that enhances detection and monitoring of the dis…

eess.IV20245 cited

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

Hongwei Bran Li, Fernando Navarro, Ivan Ezhov +77

Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a sign…

eess.IV20241 cited

Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting

Alicia Durrer, Julia Wolleb, Florentin Bieder +12

Monitoring diseases that affect the brain's structural integrity requires automated analysis of magnetic resonance (MR) images, e.g., for the evaluation of volumetric changes. Howe…

eess.IV20242 cited

Diffusion Models with Implicit Guidance for Medical Anomaly Detection

Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert +1

Diffusion models have advanced unsupervised anomaly detection by improving the transformation of pathological images into pseudo-healthy equivalents. Nonetheless, standard approach…