Alicia Durrer
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View article: Towards MR-Based Trochleoplasty Planning
Towards MR-Based Trochleoplasty Planning Open
To treat Trochlear Dysplasia (TD), current approaches rely mainly on low-resolution clinical Magnetic Resonance (MR) scans and surgical intuition. The surgeries are planned based on surgeons experience, have limited adoption of minimally i…
View article: fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting
fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting Open
Healthy tissue inpainting has significant applications, including the generation of pseudo-healthy baselines for tumor growth models and the facilitation of image registration. In previous editions of the BraTS Local Synthesis of Healthy B…
View article: Generating 3D pseudo-healthy knee MR images to support trochleoplasty planning
Generating 3D pseudo-healthy knee MR images to support trochleoplasty planning Open
Purpose: Trochlear dysplasia (TD) is a common malformation in adolescents, leading to anterior knee pain and instability. Surgical interventions such as trochleoplasty require precise planning to correct the trochlear groove. However, no s…
View article: Generating 3D Pseudo-Healthy Knee MR Images to Support Trochleoplasty\n Planning
Generating 3D Pseudo-Healthy Knee MR Images to Support Trochleoplasty\n Planning Open
Purpose: Trochlear Dysplasia (TD) is a common malformation in adolescents,\nleading to anterior knee pain and instability. Surgical interventions such as\ntrochleoplasty require precise planning to correct the trochlear groove.\nHowever, n…
View article: cWDM: Conditional Wavelet Diffusion Models for Cross-Modality 3D Medical Image Synthesis
cWDM: Conditional Wavelet Diffusion Models for Cross-Modality 3D Medical Image Synthesis Open
This paper contributes to the "BraTS 2024 Brain MR Image Synthesis Challenge" and presents a conditional Wavelet Diffusion Model (cWDM) for directly solving a paired image-to-image translation task on high-resolution volumes. While deep le…
View article: Modeling the Neonatal Brain Development Using Implicit Neural Representations
Modeling the Neonatal Brain Development Using Implicit Neural Representations Open
The human brain undergoes rapid development during the third trimester of pregnancy. In this work, we model the neonatal development of the infant brain in this age range. As a basis, we use MR images of preterm- and term-birth neonates fr…
View article: Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting
Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting Open
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. However, many of the evaluation tools are optimized for analyzi…
View article: Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection
Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection Open
The high performance of denoising diffusion models for image generation has paved the way for their application in unsupervised medical anomaly detection. As diffusion-based methods require a lot of GPU memory and have long sampling times,…
View article: WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis
WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis Open
Due to the three-dimensional nature of CT- or MR-scans, generative modeling of medical images is a particularly challenging task. Existing approaches mostly apply patch-wise, slice-wise, or cascaded generation techniques to fit the high-di…
View article: Denoising Diffusion Models for Inpainting of Healthy Brain Tissue
Denoising Diffusion Models for Inpainting of Healthy Brain Tissue Open
This paper is a contribution to the "BraTS 2023 Local Synthesis of Healthy Brain Tissue via Inpainting Challenge". The task of this challenge is to transform tumor tissue into healthy tissue in brain magnetic resonance (MR) images. This id…
View article: Memory-Efficient 3D Denoising Diffusion Models for Medical Image Processing
Memory-Efficient 3D Denoising Diffusion Models for Medical Image Processing Open
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. This limits their application to medical tasks, where we of…
View article: Diffusion Models for Contrast Harmonization of Magnetic Resonance Images
Diffusion Models for Contrast Harmonization of Magnetic Resonance Images Open
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, longitudinal comparability is essential but can be impaired by t…