Combining Deep Learning and Active Contours Opens The Way to Robust, Automated Analysis of Brain Cytoarchitectonics

  • Konstantin Thierbach
  • Pierre-Louis Bazin
  • Walter de Back
  • Filippos Gavriilidis
  • Evgeniya Kirilina
  • Carsten Jäger
  • Markus Morawski
  • Stefan Geyer
  • Nikolaus Weiskopf
  • Nico ScherfEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11046)


Deep learning has thoroughly changed the field of image analysis yielding impressive results whenever enough annotated data can be gathered. While partial annotation can be very fast, manual segmentation of 3D biological structures is tedious and error-prone. Additionally, high-level shape concepts such as topology or boundary smoothness are hard if not impossible to encode in Feedforward Neural Networks. Here we present a modular strategy for the accurate segmentation of neural cell bodies from light-sheet microscopy combining mixed-scale convolutional neural networks and topology-preserving geometric deformable models. We show that the network can be trained efficiently from simple cell centroid annotations, and that the final segmentation provides accurate cell detection and smooth segmentations that do not introduce further cell splitting or merging.


Histology Image segmentation Cell detection Deep learning Convolutional neural networks Active contours 


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Konstantin Thierbach
    • 1
  • Pierre-Louis Bazin
    • 1
    • 2
  • Walter de Back
    • 5
  • Filippos Gavriilidis
    • 1
  • Evgeniya Kirilina
    • 1
    • 3
  • Carsten Jäger
    • 1
  • Markus Morawski
    • 4
  • Stefan Geyer
    • 1
  • Nikolaus Weiskopf
    • 1
  • Nico Scherf
    • 1
    Email author
  1. 1.Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
  2. 2.University of AmsterdamAmsterdamThe Netherlands
  3. 3.Center for Cognitive Neuroscience BerlinFree University BerlinBerlinGermany
  4. 4.Paul Flechsig Institute of Brain ResearchUniversity of LeipzigLeipzigGermany
  5. 5.Institute for Medical Informatics and Biometry, TU DresdenDresdenGermany

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