3 citations · 4 across the 8 of their papers we have counts for
5 papers · 1 filter
Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis
Hadrien Reynaud, Mengyun Qiao, Mischa Dombrowski +5
Image synthesis is expected to provide value for the translation of machine learning methods into clinical practice. Fundamental problems like model robustness, domain transfer, ca…
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…
Screen Tracking for Clinical Translation of Live Ultrasound Image Analysis Methods
Simona Treivase, Alberto Gomez, Jacqueline Matthew +3
Ultrasound (US) imaging is one of the most commonly used non-invasive imaging techniques. However, US image acquisition requires simultaneous guidance of the transducer and interpr…
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…