Cyto R-CNN and CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images.

Journal: Computer methods and programs in biomedicine
PMID: 38781811

Abstract

BACKGROUND AND OBJECTIVE: Cell segmentation in bright-field histological slides is a crucial topic in medical image analysis. Having access to accurate segmentation allows researchers to examine the relationship between cellular morphology and clinical observations. Unfortunately, most segmentation methods known today are limited to nuclei and cannot segment the cytoplasm.

Authors

  • Johannes Raufeisen
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany; Institute of Medical Informatics, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany; Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Pauwelsstraße 30, 52074 Aachen, Germany.
  • Kunpeng Xie
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany; Institute of Medical Informatics, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany; Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Pauwelsstraße 30, 52074 Aachen, Germany.
  • Fabian Horst
    Department of Training and Movement Science, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, Rhineland-Palatinate, Germany.
  • Till Braunschweig
    Institute of Pathology, University Hospital RWTH Aachen, 52074 Aachen, Germany.
  • Jianning Li
    Faculty of Computer Science and Biomedical Engineering, Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria.
  • Jens Kleesiek
    AG Computational Radiology, Abteilung Radiologie, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Deutschland. j.kleesiek@dkfz-heidelberg.de.
  • Rainer Röhrig
    AKTIN-Research Group, Germany.
  • Jan Egger
    Institute for Computer Graphics and Vision, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology, Graz, Austria.
  • Bastian Leibe
    Visual Computing Institute (Computer Vision), RWTH Aachen University, Mies-van-der-Rohe Str. 15, 52074 Aachen, Germany.
  • Frank Hölzle
    Department of Oral and Maxillofacial Surgery, RWTH Aachen University Hospital, Aachen, Germany.
  • Alexander Hermans
    Visual Computing Institute (Computer Vision), RWTH Aachen University, Mies-van-der-Rohe Str. 15, 52074 Aachen, Germany.
  • Behrus Puladi
    Institute of Medical Informatics, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany; Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany.

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