30 citations · 34 across the 6 of their papers we have counts for
6 papers
Learning to learn skill assessment for fetal ultrasound scanning
Yipei Wang, Qianye Yang, Lior Drukker +3
Traditionally, ultrasound skill assessment has relied on expert supervision and feedback, a process known for its subjectivity and time-intensive nature. Previous works on quantita…
Pose-GuideNet: Automatic Scanning Guidance for Fetal Head Ultrasound from Pose Estimation
Qianhui Men, Xiaoqing Guo, Aris T. Papageorghiou +1
3D pose estimation from a 2D cross-sectional view enables healthcare professionals to navigate through the 3D space, and such techniques initiate automatic guidance in many image-g…
Show from Tell: Audio-Visual Modelling in Clinical Settings
Jianbo Jiao, Mohammad Alsharid, Lior Drukker +3
Auditory and visual signals usually present together and correlate with each other, not only in natural environments but also in clinical settings. However, the audio-visual modell…
Multimodal-GuideNet: Gaze-Probe Bidirectional Guidance in Obstetric Ultrasound Scanning
Qianhui Men, Clare Teng, Lior Drukker +2
Eye trackers can provide visual guidance to sonographers during ultrasound (US) scanning. Such guidance is potentially valuable for less experienced operators to improve their scan…
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…
Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention
Richard Droste, Yifan Cai, Harshita Sharma +4
Image representations are commonly learned from class labels, which are a simplistic approximation of human image understanding. In this paper we demonstrate that transferable repr…