48 citations · 75 across the 16 of their papers we have counts for
18 papers
Modelling Geographic Atrophy Progression using Implicit Neural Representations
Simone Sarrocco, Paul Friedrich, Florentin Bieder +4
Age-related Macular Degeneration (AMD) is the major cause of blindness in the Western world. Its late dry phase is characterised by irreversible atrophic areas, namely Geographic A…
AutoFFS: Adversarial Deformations for Facial Feminization Surgery Planning
Paul Friedrich, Florentin Bieder, Florian M. Thieringer +1
Facial feminization surgery (FFS) is a key component of gender affirmation for transgender and gender diverse patients, aiming to reshape craniofacial structures toward a female mo…
Optimizing Rank for High-Fidelity Implicit Neural Representations
Julian McGinnis, Florian A. Hölzl, Suprosanna Shit +6
Implicit Neural Representations (INRs) based on vanilla Multi-Layer Perceptrons (MLPs) are widely believed to be incapable of representing high-frequency content. This has directed…
Deep Generative Models for Enhanced Vitreous OCT Imaging
Simone Sarrocco, Philippe C. Cattin, Peter M. Maloca +2
Purpose: To evaluate deep learning (DL) models for enhancing vitreous optical coherence tomography (OCT) image quality and reducing acquisition time. Methods: Conditional Denoising…
TabINR: An Implicit Neural Representation Framework for Tabular Data Imputation
Vincent Ochs, Florentin Bieder, Sidaty el Hadramy +4
Tabular data builds the basis for a wide range of applications, yet real-world datasets are frequently incomplete due to collection errors, privacy restrictions, or sensor failures…
Towards Diagnostic Quality Flat-Panel Detector CT Imaging Using Diffusion Models
Hélène Corbaz, Anh Nguyen, Victor Schulze-Zachau +5
Patients undergoing a mechanical thrombectomy procedure usually have a multi-detector CT (MDCT) scan before and after the intervention. The image quality of the flat panel detector…
Towards MR-Based Trochleoplasty Planning
Michael Wehrli, Alicia Durrer, Paul Friedrich +5
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 o…
VidFuncta: Towards Generalizable Neural Representations for Ultrasound Videos
Julia Wolleb, Florentin Bieder, Paul Friedrich +2
Ultrasound is widely used in clinical care, yet standard deep learning methods often struggle with full video analysis due to non-standardized acquisition and operator bias. We off…
fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting
Alicia Durrer, Florentin Bieder, Paul Friedrich +3
Healthy tissue inpainting has significant applications, including the generation of pseudo-healthy baselines for tumor growth models and the facilitation of image registration. In…
MedFuncta: A Unified Framework for Learning Efficient Medical Neural Fields
Paul Friedrich, Florentin Bieder, Julian McGinnis +3
Research in medical imaging primarily focuses on discrete data representations that poorly scale with grid resolution and fail to capture the often continuous nature of the underly…
Generating 3D Pseudo-Healthy Knee MR Images to Support Trochleoplasty Planning
Michael Wehrli, Alicia Durrer, Paul Friedrich +6
Purpose: Trochlear Dysplasia (TD) is a common malformation in adolescents, leading to anterior knee pain and instability. Surgical interventions such as trochleoplasty require prec…
cWDM: Conditional Wavelet Diffusion Models for Cross-Modality 3D Medical Image Synthesis
Paul Friedrich, Alicia Durrer, Julia Wolleb +1
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…
Deep Generative Models for 3D Medical Image Synthesis
Paul Friedrich, Yannik Frisch, Philippe C. Cattin
Deep generative modeling has emerged as a powerful tool for synthesizing realistic medical images, driving advances in medical image analysis, disease diagnosis, and treatment plan…
Modeling the Neonatal Brain Development Using Implicit Neural Representations
Florentin Bieder, Paul Friedrich, Hélène Corbaz +3
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 bas…
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…
Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection
Julia Wolleb, Florentin Bieder, Paul Friedrich +3
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 method…
WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis
Paul Friedrich, Julia Wolleb, Florentin Bieder +2
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…
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…