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21 November 2019
By developing and applying new artificial intelligence methods, and advancing our knowledge on human visual perception of medical images, the investigators will improve how radiologists read breast cancer screening mammograms. Optimal reading of the screening mammograms will result in earlier detection of breast cancer, fewer healthy women recalled due to false alarms, and savings in the costs of healthcare.
Lead by Ioannis Sechopoulos, the project team consists of Jonas Teuwen, from the Department of Radiology and Nuclear Medicine, Mireille Broeders (Department for Health Evidence and the Dutch Expert Centre for Screening, LRCB), Ruud Pijnappel (UMC Utrecht and LRCB), Lucien Duijm (Canisius Wilhelmina Hospital and LRCB), and Craig Abbey and Miguel Eckstein (both from University of California, Santa Barbara, USA).
Read more on the NWO website (in Dutch).
Ioannis Sechopoulos is a member of theme Women's cancers and the LRCB, and leader of the AXTI laboratory.
By developing and applying new artificial intelligence methods, and advancing our knowledge on human visual perception of medical images, the investigators will improve how radiologists read breast cancer screening mammograms. Optimal reading of the screening mammograms will result in earlier detection of breast cancer, fewer healthy women recalled due to false alarms, and savings in the costs of healthcare.
Lead by Ioannis Sechopoulos, the project team consists of Jonas Teuwen, from the Department of Radiology and Nuclear Medicine, Mireille Broeders (Department for Health Evidence and the Dutch Expert Centre for Screening, LRCB), Ruud Pijnappel (UMC Utrecht and LRCB), Lucien Duijm (Canisius Wilhelmina Hospital and LRCB), and Craig Abbey and Miguel Eckstein (both from University of California, Santa Barbara, USA).
Read more on the NWO website (in Dutch).
Ioannis Sechopoulos is a member of theme Women's cancers and the LRCB, and leader of the AXTI laboratory.
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