PUBLICATION

Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification

Authors
Wu, T.C., Wang, X., Li, L., Bu, Y., Umulis, D.M.
ID
ZDB-PUB-210512-5
Date
2021
Source
Scientific Reports   11: 9847 (Journal)
Registered Authors
Keywords
none
MeSH Terms
  • Spatio-Temporal Analysis
  • Intravital Microscopy/methods*
  • Embryo, Nonmammalian/diagnostic imaging
  • Zebrafish
  • Signal-To-Noise Ratio
  • Cell Nucleus*
  • Developmental Biology/methods*
  • Imaging, Three-Dimensional/methods*
  • Animals
  • Algorithms
  • Models, Animal
(all 11)
PubMed
33972575 Full text @ Sci. Rep.
Abstract
Identification of individual cells in tissues, organs, and in various developing systems is a well-studied problem because it is an essential part of objectively analyzing quantitative images in numerous biological contexts. We developed a size-dependent wavelet-based segmentation method that provides robust segmentation without any preprocessing, filtering or fine-tuning steps, and is robust to the signal-to-noise ratio. The wavelet-based method achieves robust segmentation results with respect to True Positive rate, Precision, and segmentation accuracy compared with other commonly used methods. We applied the segmentation program to zebrafish embryonic development IN TOTO for nuclei segmentation, image registration, and nuclei shape analysis. These new approaches to segmentation provide a means to carry out quantitative patterning analysis with single-cell precision throughout three dimensional tissues and embryos and they have a high tolerance for non-uniform and noisy image data sets.
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Name Type Antigen Genes Isotypes Host Organism
Ab1-smadpolyclonalIgGRabbit
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Citation
Wu, T.C., Wang, X., Li, L., Bu, Y., Umulis, D.M. (2021) Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification. Scientific Reports. 11:9847.