3 citations · 7 across the 24 of their papers we have counts for
12 papers · 1 filter
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…
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…
Edge2Prompt: Modality-Agnostic Model for Out-of-Distribution Liver Segmentation
Nathan Hollet, Oumeymah Cherkaoui, Philippe C. Cattin +1
Liver segmentation is essential for preoperative planning in interventions like tumor resection or transplantation, but implementation in clinical workflows faces challenges due to…
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…