報告人： Alison Noble
Recent advances in machine learning applied to imaging are changing the way we can analyze ultrasound images and extract clinically useful information from ultrasound images and video. Ultrasound images are, after all, “just” spatial maps of acoustic patterns so we would hope that the pattern-recognition power of machine learning would be well-suited for their analysis. In this talk I will outline some recent work of my group on machine learning applied to ultrasound image analysis, some of the interesting challenges specific to this application domain, and highlight some emerging topics of research interest.
Professor Alison Noble is the Technikos Professor of Biomedical Engineering at the Institute of Biomedical Engineering, University of Oxford UK.
Professor Noble is best known for her group’s research on ultrasound image analysis much of which has involved inter-disciplinary collaborators with clinical partners. Her current interests are in machine learning applied to ultrasound imaging with application to fetal medicine in the developed world and LMICs, ranging from developing next generation tools for non-expert users of ultrasound technology, to point-of-care computer-assisted basic ultrasound assessment. Throughout her career she has maintained a keen interest in the commercialization of scientific research as a pathway to realizing impact of academic research. She co-founded and is a consultant to Intelligent Ultrasound Ltd, which became part of MedaPhor Group PLC in 2017.
Professor Noble served as the President of the Medical Image Computing and Computer-Assisted Interventions (MICCAI) Society from 2013-16. She is a European Research Council Advanced Research award holder. She is a Fellow of the Royal Academy of Engineering (2008) and a Fellow of the Royal Society (2017) and was awarded an OBE for services to science and engineering in the Queen’s Birthday Honours 2013.