PUBLICATION

Segmentation of cells from 3-d confocal images of live zebrafish embryo

Authors
Zanella, C., Rizzi, B., Melani, C., Campana, M., Bourgine, P., Mikula, K., Peyriéras, N., and Sarti, A.
ID
ZDB-PUB-071125-6
Date
2007
Source
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference   1(1): 6027-6030 (Journal)
Registered Authors
Peyriéras, Nadine, Rizzi, Barbara
Keywords
none
MeSH Terms
  • Algorithms
  • Animals
  • Artificial Intelligence
  • Embryo, Nonmammalian/cytology*
  • Humans
  • Image Enhancement/methods
  • Image Interpretation, Computer-Assisted/methods*
  • Imaging, Three-Dimensional/methods*
  • Microscopy, Confocal/methods*
  • Pattern Recognition, Automated/methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Zebrafish/anatomy & histology*
  • Zebrafish/embryology*
PubMed
18003388 Full text @ Conf. Proc. IEEE Eng. Med. Biol. Soc.
Abstract
In this paper, we use partial-differential-equation-based segmentation to accurately extract the shapes of membranes and nuclei from time lapse confocal microscopy images, taken throughout early Zebrafish embryogenesis. This strategy is a prerequisite for an accurate quantitative analysis of cell shape and morphodynamics during organogenesis and is the basis for an integrated understanding of biological processes. This data will also serve for the measurement of the variability between individuals in a population. The segmentation of cellular structures is achieved by first using an edge-preserving image filtering method for noise reduction and then applying an algorithm for cell shape reconstruction based on the Subjective Surfaces technique.
Genes / Markers
Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping