Marker-controlled watershed with deep edge emphasis and optimized H-minima transform for automatic segmentation of densely cultivated 3D cell nuclei.

Journal: BMC bioinformatics
Published Date: Jul 21, 2022

Abstract

BACKGROUND: The segmentation of 3D cell nuclei is essential in many tasks, such as targeted molecular radiotherapies (MRT) for metastatic tumours, toxicity screening, and the observation of proliferating cells. In recent years, one popular method for automatic segmentation of nuclei has been deep learning enhanced marker-controlled watershed transform. In this method, convolutional neural networks (CNNs) have been used to create nuclei masks and markers, and the watershed algorithm for the instance segmentation. We studied whether this method could be improved for the segmentation of densely cultivated 3D nuclei via developing multiple system configurations in which we studied the effect of edge emphasizing CNNs, and optimized H-minima transform for mask and marker generation, respectively.

Authors

  • Tuomas Kaseva
    HUS Medical Imaging Center, Radiology, Helsinki University Hospital and University of Helsinki, P.O. Box 340, FI-00290, Helsinki, Finland.
  • Bahareh Omidali
    Department of Physics, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland.
  • Eero Hippeläinen
    Department of Physics, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland.
  • Teemu Mäkelä
    HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland; Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland.
  • Ulla Wilppu
    HUS Medical Imaging Center, Radiology, Helsinki University Hospital and University of Helsinki, P.O. Box 340, FI-00290, Helsinki, Finland.
  • Alexey Sofiev
    HUS Medical Imaging Center, Radiology, Helsinki University Hospital and University of Helsinki, P.O. Box 340, FI-00290, Helsinki, Finland.
  • Arto Merivaara
    Division of Pharmaceutical Biosciences, Faculty of Pharmacy, Centre for Drug Research, University of Helsinki, Helsinki, Finland.
  • Marjo Yliperttula
    Division of Pharmaceutical Biosciences, Faculty of Pharmacy, Centre for Drug Research, University of Helsinki, Helsinki, Finland.
  • Sauli Savolainen
    HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340 (Haartmaninkatu 4), FI-00290, Helsinki, Finland.
  • Eero Salli
    HUS Medical Imaging Center, Radiology, Helsinki University Hospital and University of Helsinki, P.O. Box 340, FI-00290, Helsinki, Finland. eero.salli@hus.fi.

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