Inferring a third spatial dimension from 2D histological images

Maxime W. Lafarge, Josien P.W. Pluim, Koen A.J. Eppenhof, Pim Moeskops, Mitko Veta

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)


Histological images are obtained by transmitting light through a tissue specimen that has been stained in order to produce contrast. This process results in 2D images of the specimen that has a three-dimensional structure. In this paper, we propose a method to infer how the stains are distributed in the direction perpendicular to the surface of the slide for a given 2D image in order to obtain a 3D representation of the tissue. This inference is achieved by decomposition of the staining concentration maps under constraints that ensure realistic decomposition and reconstruction of the original 2D images. Our study shows that it is possible to generate realistic 3D images making this method a potential tool for data augmentation when training deep learning models.

Original languageEnglish
Title of host publication2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
Place of PublicationPiscataway
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)978-1-5386-3636-7
ISBN (Print)978-1-5386-3637-4
Publication statusPublished - 23 May 2018
Event15th IEEE International Symposium on Biomedical Imaging (ISBI 2018) - Omni Shoreham Hotel, Washington, United States
Duration: 4 Apr 20187 Apr 2018
Conference number: 15


Conference15th IEEE International Symposium on Biomedical Imaging (ISBI 2018)
Abbreviated titleISBI18
Country/TerritoryUnited States
Internet address


  • 3D Inference
  • Adversarial Training
  • Histopathology Image Analysis
  • Image Synthesis


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