3 citations · 3 across the 6 of their papers we have counts for
10 papers · 1 filter
Can non-specialists provide high quality gold standard labels in challenging modalities?
Samuel Budd, Thomas Day, John Simpson +5
Probably yes. -- Supervised Deep Learning dominates performance scores for many computer vision tasks and defines the state-of-the-art. However, medical image analysis lags behind…
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…
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…
Weakly Supervised Localisation for Fetal Ultrasound Images
Nicolas Toussaint, Bishesh Khanal, Matthew Sinclair +4
This paper addresses the task of detecting and localising fetal anatomical regions in 2D ultrasound images, where only image-level labels are present at training, i.e. without any…
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…