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Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
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Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

DOI:
10.3791/58543-v

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08:59 min

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October 28, 2018

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, , , , , , ,
1Department of Chemical and Product Safety,German Federal Institute for Risk Assessment (BfR), 2Deutsches Rheuma-Forschungszentrum (DRFZ) Berlin, a Leibniz Institute, 3Charité Universitätsmedizin Berlin, 4Applied Systems Biology,Leibniz Institute for Natural Product Research and Infection Biology Hans Knöll Institute

章

  • 00:04標題
  • 01:11Reconstruct the 3D Image
  • 03:13Transform the 3D Reconstructed Surfaces into 2D Projections
  • 04:28Find the Periphery and Calculate the Fourier Components using Fiji
  • 05:13Self-Organizing Maps
  • 06:53Results: Robustness of SOM Mapping Approach
  • 08:32Conclusion

概要

自動翻訳

自動翻訳

Here, we provide a workflow that allows the identification of healthy and pathological cells based on their 3-dimensional shape. We describe the process of using 2D projection outlines based on the 3D surfaces to train a Self-Organizing Map that will provide objective clustering of the investigated cell populations.

タグ

Morphology-based DistinctionFourier TransformsSelf-organizing Maps3D MicroscopyCell ReconstructionSurface CreationSmoothingThresholdingがん研究免疫学DiagnosisTherapy

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