271 citations · 307 across the 18 of their papers we have counts for
18 papers
Learning Physics-Inspired Regularization for Medical Image Registration with Hypernetworks
Anna Reithmeir, Julia A. Schnabel, Veronika A. Zimmer
Medical image registration aims at identifying the spatial deformation between images of the same anatomical region and is fundamental to image-based diagnostics and therapy. To da…
A skeletonization algorithm for gradient-based optimization
Martin J. Menten, Johannes C. Paetzold, Veronika A. Zimmer +6
The skeleton of a digital image is a compact representation of its topology, geometry, and scale. It has utility in many computer vision applications, such as image description, se…
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space
Veronika Spieker, Wenqi Huang, Hannah Eichhorn +7
Motion-resolved reconstruction for abdominal magnetic resonance imaging (MRI) remains a challenge due to the trade-off between residual motion blurring caused by discretized motion…
Using UK Biobank data to establish population-specific atlases from whole body MRI
Sophie Starck, Vasiliki Sideri-Lampretsa, Jessica J. M. Ritter +4
Reliable reference data in medical imaging is largely unavailable. Developing tools that allow for the comparison of individual patient data to reference data has a high potential…
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View
Veronika A. Zimmer, Alberto Gomez, Emily Skelton +10
Automatic segmentation of the placenta in fetal ultrasound (US) is challenging due to the (i) high diversity of placenta appearance, (ii) the restricted quality in US resulting in…
PRETUS: A plug-in based platform for real-time ultrasound imaging research
Alberto Gomez, Veronika A. Zimmer, Gavin Wheeler +8
We present PRETUS -a Plugin-based Real Time UltraSound software platform for live ultrasound image analysis and operator support. The software is lightweight; functionality is brou…
AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs
Lei Li, Veronika A. Zimmer, Julia A. Schnabel +1
Left atrial (LA) segmentation from late gadolinium enhanced magnetic resonance imaging (LGE MRI) is a crucial step needed for planning the treatment of atrial fibrillation. However…
Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review
Lei Li, Veronika A. Zimmer, Julia A. Schnabel +1
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) is commonly used to visualize and quantify left atrial (LA) scars. The position and extent of scars provide importa…
Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging
Qingjie Meng, Jacqueline Matthew, Veronika A. Zimmer +4
Deep neural networks exhibit limited generalizability across images with different entangled domain features and categorical features. Learning generalizable features that can form…
Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information
Lei Li, Veronika A. Zimmer, Wangbin Ding +4
Deep learning (DL)-based models have demonstrated good performance in medical image segmentation. However, the models trained on a known dataset often fail when performed on an uns…
AtrialJSQnet: A New Framework for Joint Segmentation and Quantification of Left Atrium and Scars Incorporating Spatial and Shape Information
Lei Li, Veronika A. Zimmer, Julia A. Schnabel +1
Left atrial (LA) and atrial scar segmentation from late gadolinium enhanced magnetic resonance imaging (LGE MRI) is an important task in clinical practice. %, to guide ablation the…
Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time
Cesare Magnetti, Veronika Zimmer, Nooshin Ghavami +6
We present a computational method for real-time, patient-specific simulation of 2D ultrasound (US) images. The method uses a large number of tracked ultrasound images to learn a fu…
A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology
James R. Clough, Nicholas Byrne, Ilkay Oksuz +3
We introduce a method for training neural networks to perform image or volume segmentation in which prior knowledge about the topology of the segmented object can be explicitly pro…
Mechanically Powered Motion Imaging Phantoms: Proof of Concept
Alberto Gomez, Cornelia Schmitz, Markus Henningsson +8
Motion imaging phantoms are expensive, bulky and difficult to transport and set-up. The purpose of this paper is to demonstrate a simple approach to the design of multi-modality mo…
Robotic-assisted Ultrasound for Fetal Imaging: Evolution from Single-arm to Dual-arm System
Shuangyi Wang, James Housden, Yohan Noh +20
The development of robotic-assisted extracorporeal ultrasound systems has a long history and a number of projects have been proposed since the 1990s focusing on different technical…
Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging
Qingjie Meng, Matthew Sinclair, Veronika Zimmer +11
Detecting acoustic shadows in ultrasound images is important in many clinical and engineering applications. Real-time feedback of acoustic shadows can guide sonographers to a stand…
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers
Bishesh Khanal, Alberto Gomez, Nicolas Toussaint +11
Ultrasound (US) is the most widely used fetal imaging technique. However, US images have limited capture range, and suffer from view dependent artefacts such as acoustic shadows. C…
Adapted and Oversegmenting Graphs: Application to Geometric Deep Learning
Alberto Gomez, Veronika A. Zimmer, Bishesh Khanal +2
We propose a novel iterative method to adapt a a graph to d-dimensional image data. The method drives the nodes of the graph towards image features. The adaptation process naturall…