How does it work – Professor Ken Young, Head of Research (NCCPM), Medical Physics Department, Royal Surrey County Hospital

This talk will enable delegates to understand:
• The basics of how AI models learn to interpret images.
• How AI has been developed for breast screening.
• How AI Deep Learning Computer Aided Detection (CAD) differs from traditional CAD.
• The stages in implementing AI tools for breast screening.

Professor Ken Young led the National Coordinating Centre for the Physics of Mammography (NCCPM) from 1990 to 2019. He currently leads research at NCCPM, and is a Visiting Professor of Medical Physics at the University of Surrey. He led the OPTIMAM research projects funded by Cancer Research UK which created the OPTIMAM Image Database; one of the world’s largest mammography image databases, which is shared with leading academic research groups and commercial companies. Collaboration in the development and evaluation of artificial intelligence techniques to automate breast cancer detection is a major focus of his current research.

Evidence – Professor Nico Karssemeijer, Founder ScreenPoint and Professor of Radiology, Radboud University, Nijmegen, The Netherlands

Professor Nico Karssemeijer is professor of Computer Aided Diagnosis (CAD) at the Radboud University Nijmegen and CEO and co-founder and CEO of ScreenPoint Medical. He studied physics at Delft University of Technology and graduated at the Radboud University Nijmegen in 1989. The research group he formed at Radboud University Medical Centre gained worldwide recognition for its pioneering work in breast imaging and computer aided diagnosis. He served as associate editor of IEEE Transactions on Medical Imaging, was member of the executive editorial board of Physics in Medicine and Biology, and member of the editorial boards of Medical Image Analysis and Journal of Medical Imaging. He also served as symposium chair of SPIE Medical Imaging and was member of the scientific program committee of RSNA.

From 1996 to 2008 Nico Karssemeijer was consultant of the Silicon Valley based company R2 Technology and made major contributions to the ImageChecker, which was for two decades the most widely used CAD system in radiology. He was principal investigator in the EU funded projects SCREEN and SCREEN-TRIAL, which had a strong impact on digitisation of breast screening programs and was coordinator of the H2020 project ASSURE on technology development for personalised breast screening.

In 2014 Nico Karssemeijer founded ScreenPoint Medical BV in Nijmegen, The Netherlands, which develops AI solutions for breast imaging. He is also co-founder of Volpara Health Technologies (Wellington, NZ), a company that provides solutions for quality and workflow improvement, and QView Medical Inc. (Los Altos, CA, USA), which develops AI for automated breast ultrasound.

Where can it fit into the clinical pathway – Dr Louise Wilkinson, Consultant Radiologist, Oxford Breast Imaging Centre

Dr Louise Wilkinson is a consultant breast radiologist in Oxford and was previously Director of Screening of South West London Breast Screening Service. She enjoys teaching and has worked with many enthusiastic junior radiologists who have subsequently specialised in breast radiology. She has been involved with quality assurance at regional and national levels for over a decade. As a member of the Optimam steering group, she has developed an interest in how technology can support the breast screening pathway, but feels strongly that the implementation of AI should be carefully planned to minimise risk as we change the way we work.

Information Governance & AI – Dr Kevin Dunbar, Regional Head of Screening Quality Assurance Service (SQAS) – South, Public Health England Screening Division