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U-Net: deep learning for cell counting, detection, and morphometry

Nature Methods · 2018 · Vol. 16(1) · pp. 67–70

Thorsten Falk✉(University of Freiburg)Dominic Mai(University of Freiburg)Robert Bensch(University of Freiburg)Özgün Çiçek(University of Freiburg)Ahmed Abdulkadir(University of Bern)Yassine Marrakchi(University of Freiburg)Anton Böhm(University of Freiburg)Jan Deubner(University of Freiburg)Zoë Jäckel(Brain (Germany))Katharina Seiwald(University of Freiburg)Alexander Dovzhenko(University of Freiburg)Olaf Tietz(University of Freiburg)Cristina Dal Bosco(University of Freiburg)Seán Walsh(University of Freiburg)Deniz Saltukoglu(University Medical Center Freiburg)Tuan Leng Tay(Bernstein Center for Computational Neuroscience Freiburg)Marco Prinz(University of Freiburg)Klaus Palme(University of Freiburg)Matias Simons(Université Paris Cité)Ilka Diester(Bernstein Center for Computational Neuroscience Freiburg)Thomas Brox(Bernstein Center for Computational Neuroscience Freiburg)Olaf Ronneberger(University of Freiburg)

Cell Image Analysis Techniques AI in cancer detection Digital Imaging for Blood DiseasesPlug-inDeep learningComputer scienceSegmentationArtificial intelligenceCloud computingImage segmentationNet (polyhedron)Pattern recognition (psychology)Machine learning