Artificial Defocus for Displaying Markers in Microscopy Z-Stacks

  • Authors:
  • Alessandro Giusti;Pierluigi Taddei;Giorgio Corani;Luca Gambardella;Cristina Magli;Luca Gianaroli

  • Affiliations:
  • Dalle Molle Institute for Artificial Intelligence, Lugano, Switzerland;JRC, Ispra;Dalle Molle Institute for Artificial Intelligence, Lugano, Switzerland;Dalle Molle Institute for Artificial Intelligence, Lugano, Switzerland;International Institute of Reproductive Medicine, Lugano, Switzerland;International Institute of Reproductive Medicine, Lugano, Switzerland

  • Venue:
  • IEEE Transactions on Visualization and Computer Graphics
  • Year:
  • 2011

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Abstract

As microscopes have a very shallow depth of field, Z-stacks (i.e. sets of images shot at different focal planes) are often acquired to fully capture a thick sample. Such stacks are viewed by users by navigating them through the mouse wheel. We propose a new technique of visualizing 3D point, line or area markers in such focus stacks, by displaying them with a depth-dependent defocus, simulating the microscope's optics; this leverages on the microscopists' ability to continuously twiddle focus, while implicitly performing a shape-from-focus reconstruction of the 3D structure of the sample. User studies confirm that the approach is effective, and can complement more traditional techniques such as color-based cues. We provide two implementations, one of which computes defocus in real time on the GPU, and examples of their application.