ScreenPoint develops Deep Learning and image analysis technology for automated reading of mammograms and digital breast tomosynthesis. We exploit the latest methods in the rapidly evolving field of machine learning, combining these with very large well curated digital image databases and a thorough understanding of the physics of mammogram image formation and the practicalities of the clinical deployment of mammographic image analysis.
ScreenPoint has its roots in the Diagnostic Image Analysis Group (DIAG) of the Radboud University Medical Center in Nijmegen, The Netherlands. DIAG is recognized as a worldwide leader in the development of AI and deep learning applications in medical imaging. Over a period of 25 years, breast image analysis techniques were developed by Professor Nico Karssemeijer and his team, resulting in over 150 peer reviewed scientific papers on topics including mammography CAD, breast density, breast cancer screening, breast ultrasound, MRI, and digital pathology. As a result of continued innovation, algorithms for detection and diagnosis of breast cancer are now reaching unprecedented levels of performance. Researchers in DIAG were among the first to publish on deep learning in mammography.