Segmentation of Cells from 3-D Confocal Images of Live Zebrafish Embryo

Abstract

In this paper, we use partial-differential-equationbased 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.

Creating 3D Digital Replicas of Ascidian Embryos from Stacks of Confocal Images

“…The major limiting step for the automatic reconstruction of these embryos is the fact that membranes located in, or close to, the x-y imaging planes are either missed or imaged with very low intensity. The recent development of DSLM, which allows imaging of embryos from several directions (Keller et al 2008), should greatly alleviate this difficulty and allow efficient application of automatic 3D segmentation algorithms (e.g., Zanella et al 2007). Once these replicas are imported in 3D Virtual Embryo (Tassy et al 2006) individual cells or subpopulations of cells can be analyzed and compared at a given developmental stage or between stages.…”

3-D Zebrafish Embryo Image Filtering by Nonlinear Partial Differential Equations

“…Although (7) removes slightly better the noise, the membranes appear blurred and part of the information is lost. We verified in [14] that such information about boundaries is important to correctly segment the membranes. Mathematical reliability of such nonlinear models for image processing where the edge indicator may depend on image intensity is given in [16].…”

“…The image filtering has to be always a first step in a chain of image processing operations, and it is very important to design appropriate filters and chose their optimal parameters for any particular type of data. The goal of this paper is to apply the methods of nonlinear diffusion filtering to 3-D confocal images [1] of zebrafish embryogenesis in order to perform the segmentation [14] and the tracking [15] nadine.peyrieras@inaf.cnrs-gif.fr cells. The filtering models are discussed in section II.…”

Region‐Based PDEs for Cells Counting and Segmentation in 3D+Time Images of Vertebrate Early Embryogenesis

“…The zebrafish (Danio Rerio) is a model organism extensively studied to explore the gene function and vertebrate development [ 2 – 7 ] and might soon become a major model organism for preclinical drug testing by pharmaceutical industries. Although distant from humans, nevertheless it has comparable organs and tissues and may supplement higher vertebrate models.…”