30 citations · 54 across the 6 of their papers we have counts for
9 papers
A Dual Adversarial Calibration Framework for Automatic Fetal Brain Biometry
Yuan Gao, Lok Hin Lee, Richard Droste +4
This paper presents a novel approach to automatic fetal brain biometry motivated by needs in low- and medium- income countries. Specifically, we leverage high-end (HE) ultrasound i…
Self-Supervised Ultrasound to MRI Fetal Brain Image Synthesis
Jianbo Jiao, Ana I. L. Namburete, Aris T. Papageorghiou +1
Fetal brain magnetic resonance imaging (MRI) offers exquisite images of the developing brain but is not suitable for second-trimester anomaly screening, for which ultrasound (US) i…
Self-supervised Contrastive Video-Speech Representation Learning for Ultrasound
Jianbo Jiao, Yifan Cai, Mohammad Alsharid +3
In medical imaging, manual annotations can be expensive to acquire and sometimes infeasible to access, making conventional deep learning-based models difficult to scale. As a resul…
Automatic Probe Movement Guidance for Freehand Obstetric Ultrasound
Richard Droste, Lior Drukker, Aris T. Papageorghiou +1
We present the first system that provides real-time probe movement guidance for acquiring standard planes in routine freehand obstetric ultrasound scanning. Such a system can contr…
Self-supervised Representation Learning for Ultrasound Video
Jianbo Jiao, Richard Droste, Lior Drukker +2
Recent advances in deep learning have achieved promising performance for medical image analysis, while in most cases ground-truth annotations from human experts are necessary to tr…
Discovering Salient Anatomical Landmarks by Predicting Human Gaze
Richard Droste, Pierre Chatelain, Lior Drukker +3
Anatomical landmarks are a crucial prerequisite for many medical imaging tasks. Usually, the set of landmarks for a given task is predefined by experts. The landmark locations for…