PUBLICATION

Methods toward in vivo measurement of zebrafish epithelial and deep cell proliferation

Authors
Campana, M., Maury, B., Dutreix, M., Peyriéras, N., and Sarti, A.
ID
ZDB-PUB-090929-14
Date
2010
Source
Computer methods and programs in biomedicine   98(2): 103-117 (Journal)
Registered Authors
Peyriéras, Nadine
Keywords
Automatic cell classification, Cell density, Cell proliferation, Biomedical image processing
MeSH Terms
  • Algorithms
  • Animals
  • Cell Count/statistics & numerical data
  • Cell Proliferation
  • Epithelial Cells/classification
  • Epithelial Cells/cytology
  • Epithelium/embryology
  • Image Processing, Computer-Assisted/methods*
  • Image Processing, Computer-Assisted/statistics & numerical data
  • Imaging, Three-Dimensional
  • Zebrafish/embryology*
PubMed
19781805 Full text @ Comput. Methods Programs Biomed.
Abstract
We present a strategy for automatic classification and density estimation of epithelial enveloping layer (EVL) and deep layer (DEL) cells, throughout zebrafish early embryonic stages. Automatic cells classification provides the bases to measure the variability of relevant parameters, such as cells density, in different classes of cells and is finalized to the estimation of effectiveness and selectivity of anticancer drug in vivo. We aim at approaching these measurements through epithelial/deep cells classification, epithelial area and thickness measurement, and density estimation from scattered points. Our procedure is based on Minimal Surfaces, Otsu clustering, Delaunay Triangulation, and Within-R cloud of points density estimation approaches. In this paper, we investigated whether the distance between nuclei and epithelial surface is sufficient to discriminate epithelial cells from deep cells. Comparisons of different density estimators, experimental results, and extensively accuracy measurements are included.
Genes / Markers
Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping