LABORATORY OF BIOLOGICAL DIVERSITYOHTA GroupSpecially Appointed Assistant Professor:
OHTA, Yusaku

Image analysis is an important component of understanding
life sciences. It enables us to quantify phenomena by extracting meaningful information from a large number of images
and to properly represent that information. I am developing
image analysis techniques aimed at analyzing the developmental process of early zebrafish embryo at whole embryo
scale and single-cell resolution. Currently, I am developing an analysis technique that can simultaneously extract
multiple pieces of information such as cell morphology, cell
motility, and cell dynamics by combining 3D cell tracking
and functional imaging.

I. Simultaneous multifunctional analysis of early
embryonic development at a whole embryo
scale and single cell resolution.

Three-dimensional remodeling of cell populations throughcell migration is essential in early embryogenesis. Cell
migration is highly coordinated by controlling cell-celladhesion. To elucidate the principles of such complex
embryogenesis, it is necessary to understand the cellular
dynamics of the whole embryo at single cell resolution. I amFigure 1. Simultaneous multifunctional analysis of early embryonicdevelopment

developing image analysis techniques to analyze the developmental process of early zebrafish embryogenesis at wholeembryo scale and single-cell resolution.
With the development of microscopy, imaging of early
embryonic imaging has evolved from two-dimensional,
embryonic development has evolved from two-dimensional,
fixed specimen and partial embryo observation to threedimensional, living specimen and whole embryo scale.
This evolution has led to an explosion in the analysis ofcell migration during the development of early embryos inrecent years. However, conventional image analysis techniques could only extract information on cell migration inearly development. Therefore, I have developed an analysis
method that can simultaneously extract information on cell
migration, cell dynamics, and cell morphology at whole
embryo scale and single cell resolution.

II. Research support by image analysis

The development of imaging technology in life science
research has been remarkable, allowing many researchers toeasily acquire large and complex image data sets. However,image analysis is still a hurdle for researchers and can becomea research bottleneck. To solve this problem, I provide
research support based on the following three concepts.
The first concept is quantitative image analysis based on
extensive knowledge of image processing and statistics. For
most researchers, image evaluation is limited to qualitativeand subjective analysis. Correct analysis based on knowledgeof image and statistics supports quantitative and objectiveanalysis. The second concept is to support image analysis
through machine learning, including deep learning. Machinelearning has made remarkable progress in recent years,
and with a little learning, it is possible to simplify analysis,
which has been difficult with conventional image analysis
techniques. The third concept relates to providing researcherswith easy-to-understand explanations of image analysis techniques on the Web. The content ranges from the principles
of image analysis methods to how to use image analysis
software and plug-ins.

Figure 2. A website that explains how to use image analysis software

67