Quantifying Image Structures in High-Throughput Microscopy with Total Variation Flow

Shekoufeh Gorgi Zadeh, Max Hermann, Elisa Merklinger, Jan-Gero Schloetel, and Thomas Schultz
In proceedings of IEEE Symp. Biomedical Imaging (ISBI), 2016
 

Abstract

A recurrent problem in the analysis of microscopy images is to quantify the number and size of spots on a homogeneous background. Unfortunately, segmenting the individual spots becomes unreliable when they are close together, or when the image contains noise and artifacts. On the other hand, manual counting and line-scan measurements are prone to bias and too time-consuming to be used in high-throughput microscopy. In this work, we derive novel per-pixel measures of spot scale and density from Total Variation Flow, a partial differential equation that changes the intensities of image regions at a rate inverse to their scale. On simulated, phantom, and real-world data from Stimulated Emission Depletion (STED) microscopy, we demonstrate the robustness of our novel method relative to a standard segmentation-based approach.

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Bibtex

@INPROCEEDINGS{GorgiZadeh:ISBI16,
     author = {Gorgi Zadeh, Shekoufeh and Hermann, Max and Merklinger, Elisa and Schloetel, Jan-Gero and Schultz,
               Thomas},
      title = {Quantifying Image Structures in High-Throughput Microscopy with Total Variation Flow},
  booktitle = {IEEE Symp. Biomedical Imaging (ISBI)},
       year = {2016},
       note = {Accepted for publication.},
   abstract = {A recurrent problem in the analysis of microscopy images is to quantify the number and size of spots
               on a homogeneous background. Unfortunately, segmenting the individual spots becomes unreliable when
               they are close together, or when the image contains noise and artifacts. On the other hand, manual
               counting and line-scan measurements are prone to bias and too time-consuming to be used in
               high-throughput microscopy. In this work, we derive novel per-pixel measures of spot scale and
               density from Total Variation Flow, a partial differential equation that changes the intensities of
               image regions at a rate inverse to their scale. On simulated, phantom, and real-world data from
               Stimulated Emission Depletion (STED) microscopy, we demonstrate the robustness of our novel method
               relative to a standard segmentation-based approach.}
}