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Quantification and Spatial Relationship

This study explores the intricate processes of quantification and spatial relationships in image analysis, focusing on perception, recognition, and differentiation. We examine how qualitative terms relate to quantitative measurements through digitization and segmentation techniques. The methodology encompasses measuring various attributes of objects, including size, shape, and spatial arrangements, with examples from biological contexts such as bacterial growth and fungal colonies. The findings offer insights into the ontology of objects and their interactions, contributing to a deeper understanding of image analysis's role in scientific research.

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Quantification and Spatial Relationship

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  1. g Forschungszentrum Quantification and Spatial Relationship Karsten Rodenacker, Neuherberg Martina Hausner, München Anna A. Gorbushina, Oldenburg

  2. Content • Introduction from perception to image analysis • Measurement objects, groups of objects inter- and intra-relationships • Examples • Conclusion

  3. Introduction • Perception – recognition – differentiation – description • Quantification • Relation of qualitative and quantitative terms

  4. Introduction • The difficulty NOT to see something

  5. Introduction • The difficulty to see anything

  6. Introduction • The ease to see the impossible

  7. Introduction • Quantitative terms

  8. Introduction • How to relate qualitative and quantitative terms?

  9. Introduction • Digitisation • Segmentation

  10. Introduction • Sub sectioning and change of scale

  11. Introduction Measurement (of one object) • Extension • Size • Shape • Structure

  12. Introduction Measurement (of several objects) • Arrangement • Relation • Neighbourhood

  13. Measurement • Examples of measurements,objects and groups of objects • Spatial relationships

  14. Measurement • Area • Perimeter • Extension

  15. Measurement • Shape • Growth shape • Density, intensity

  16. Measurement • ExtensionsLength (skeleton)=1621 pxmean thickness=2.27 px

  17. Measurement • Neighbourhoodclosing onfilaments

  18. Measurement • SpatialRelationshipDelaunay triangulationnearest neighboursminimum spanning treeconvex hullSkeleton neighbourhood

  19. Measurement • SpatialRelationshipExample frompathology

  20. Measurement • Spatial relationship (objects of different type) Double marked sludge flocks Distances to the red phase

  21. object object object object object Measurement • Measurement continuum • Measurement hierarchy pixel content location properties content location external properties

  22. Example • Bacterial growth in flow chambersDifferentiation of wild and mutant bacteria pseudomonas aeruginosa by CLSM imaging

  23. Example • Wild (PA) and mutant (MW) bacteriaGrowth overtime(slice # = depth)

  24. Example • Substrate coverage (closing) Wild type bacteria Mutant bacteria

  25. Example • Bacterial growth in flow chambersConjugativegenetic transfer in bacterialbiofilm

  26. Example • Quantification of colonies of micro colonial fungi from sub aerial biofilms coniosporium sp. and sarcinomyces sp. under soil (b), sand (s) coverage and in air (l)

  27. Example • Colonies of micro colonial fungi

  28. Example • Colonies of micro colonial fungi

  29. Conclusion • Perception, descriptionand measurement of objects and object groups in images • Exclusions (e.g. texture, filtering, fractals, etc.) • Faith and (apparent) truth

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