Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance.

Abstract

Authors

• Laura Kerschke
  Institute of Biostatistics and Clinical Research, IBKF, University of Muenster, Schmeddingstrasse 56, 48149, Muenster, Germany. laura.kerschke@ukmuenster.de.
• Stefanie Weigel
  Clinic for Radiology and Reference Center for Mammography Muenster, University of Muenster and University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
• Alejandro Rodríguez-Ruiz
  From the Department of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB Nijmegen, Geert Grooteplein 10, 6525 GA, Post 766, Nijmegen, the Netherlands (A.R.R., I.S., R.M.M.); Department of Radiology & Imaging Sciences, Emory University, Atlanta, Ga (E.K.); ScreenPoint Medical BV, Nijmegen, the Netherlands (J.J.M.); Lynn Women's Health & Wellness Institute, Boca Raton Regional Hospital, Boca Raton, Fla (K.S.); Referenzzentrum Mammographie Munich, Brustdiagnostik München and FFB, Munich, Germany (S.H.H.); and Dutch Expert Centre for Screening, Nijmegen, the Netherlands (I.S.).
• Nico Karssemeijer
• Walter Heindel
  Department of Clinical Radiology, University of Muenster, Muenster, Germany.

Keywords

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