Jacqueline Matthew
Guy's and St Thomas' NHS Foundation Trust, King's College London
Papers
3
Total Citations
80
H-Index
3
About
Jacqueline Matthew is a leading researcher at the intersection of robotics, artificial intelligence, and medical imaging, with a primary focus on advancing fetal ultrasound technology. Her work addresses critical limitations in conventional prenatal imaging, particularly the variability and operator-dependence of manual ultrasound scans. Matthew’s major contributions center on the development of robotic-assisted ultrasound systems, pioneering the evolution from single-arm to dual-arm robotic platforms for fetal imaging. Her 2019 paper on this transition, which has garnered 45 citations, laid the groundwork for more stable, reproducible, and comprehensive fetal assessments. Building on this, her 2021 work (32 citations) introduced a standardized acquisition workflow using a dual-probe robot, aiming to enhance diagnostic reliability and usability through automation and AI integration. By enabling consistent, high-quality imaging regardless of operator skill, Matthew’s research promises to democratize access to expert-level prenatal diagnostics. Her achievements represent a significant step toward making robotic ultrasound a practical clinical tool, with the potential to improve outcomes for expectant mothers and their babies worldwide.
Research Focus
Key Achievements
Top Papers
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