
Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/565 |
Project. Our goal is to use in toto imaging of developing transgenic zebrafish embryos on a genomic scale
to acquire digital, quantitative, cell-based, molecular data suitable for modelling the biological circuits
that turn an egg into an embryo. In toto imaging uses confocal/2-photon microscopy to capture the
entire volume of organs and eventually whole embryos at cellular resolution every few minutes in living
specimens thoughout their development. The embryos are labelled such that nuclei are one color and cell
membranes another color to allow cells to be segmented and tracked as they move and divide. The use
of a transgenic marker in a third color allows a variety of molecular data to be marked. In toto imaging
generates 4-d image sets (xyzt) which can contain 100,000 to 1,000,000 images per experiment. We are
developing a software package called GoFigure to visualize, segment, and analyze these very large image
sets. GoFigure uses a MySQL database back end for managing storage of images and segmented objects
and uses VTK and ITK for visualization and segmentation. We plan to use in toto imaging to digitize the
complete expression and subcellular localization patterns of thousands of proteins throughout zebrafish
embryogenesis. This genomic data, our zebrafish lines, and GoFigure will be distributed following the
Open Data/Open Source model.







Summary:
The authors describe the The Digital Fish Project, which involve the in vivo imaging of full Zebra fish embryos using a 2 photon confocal microscope, and the GoFigure software, used to segment the cells and the nuclei, track them over the time, visualize the acquired images, ...
Open Science:
The paper, the data and the software are licensed with an open source license.
Reproducibility:
GoFigure is currently usable only on the windows OS, an OS I'm not used to using. I haven't built the code.
Use of Open Source Software:
Yes. ITK, VTK and CMake are used. The authors are also planning to use KWWidgets.
Open Source Contributions:
Yes. The source code is fully available with subversion.
Code Quality:
The code seem well structured and documented (That's also the Ohoh point of view http://www.ohloh.net/projects/8464?p=GoFigure).
Applicability to other problems:
In toto imaging is one of the most interesting thing to study the embryogenesis. This software, as well as the biological methods used, will be very useful to study the embryogenesis in other species. We can also imagine using it to study the differenciation of the cells in some particular tissues.
Requests for additional information from authors:
What image format comes from your microscope? It is usualy a bit difficult to read proprietary format of the biggest confocal manufacturers, and if a new reader have been developed, in may be one other good thing to reuse from this project.
Confocal imaging usually have an extinction of the signal when the depth increase. Don't you have that phenomenon in your images? If yes, have you leave correct it? How?
You say the image are noisy. How are you denoising them?
Finall, you say that "the amount of the expression marker in each cell can then be quantitated". However, from my own experience, quantitation is very difficult in confocal images, because it is highly dependent of several factors (gain and offset of the detector, transparency of the object and/or the medium, depth extinction, photo blitching, ...). Can you say more about what you want to measure, and how you will do that ?
Additional Comments:
A very promising project - I will follow it closely!
Comment by Alexandre Gouaillard: good svn server address

http://iorich.caltech.edu/public/svn/gofigure/trunk/
Comment by Alexandre Gouaillard: answers from the author

gaethan,
the data are definitly available on that same site. Please follow one of the two links given on the paper for the data.
The zebrafish dataaset have been one of the first to be publicly available.
> What image format comes from your microscope? It is usually a bit difficult to read proprietary format of the biggest confocal manufacturers, and if a new reader have been developed, in may be one other good thing to reuse from this project.
There are quite a few different formats indeed. One of them is LSM and we are planning to improve the ITK LSM reader if necessary. Any reader that would be developed would be transfered to ITK.
> Confocal imaging usually have an extinction of the signal when the depth increase. Don't you have that phenomenon in your images? If yes, have you leave correct it? How?
That's indeed a very common phenomenon in confocal images. We are planning to address this issue, but shouldn't start working on it before mid 2008.
> You say the image are noisy. How are you denoising them?
For the time being we are using wavelet coefficient thresholding. it's automatic, brutal, and does not make any assumption on the underlying object.
Some researchers from university of Iowa have reported good signal enhancement using gaussian fitting. It's less brutal, and is well adapted to cell nuclei segmentation.
An approach we would like to experiment in the future is noise distribution computation: you select a part of the image you know being the background. You know that any signal here is only noise. You can then compute the distribution of the noise and, supposing the noise is an additive signal, remove the noise from the rest of the dataset. This method proved to be very successfull in geodesic signals denoising, where they could identify the noise in the signal prior to the shock wave pattern.
>Finally, you say that "the amount of the expression marker in each cell can then be quantitated". However, from my own experience, quantitation is very difficult in confocal images, because it is highly dependent of several factors (gain and offset of the detector, transparency of the object and/or the medium, depth extinction, photo blitching, ...). Can you say more about what you want to measure, and how you will do that ?
:-) Right, it's indeed quite challenging, and we don't have a satisfactory algorithm for that, yet.
In our case though , we always work with the same object: zebrafish. We are thinking, with the microscope researchers, about studying the optical properties of the zebrafish more in detail. That would help us compensate (for zebrafish) the loss in intensity along Z in the software (post acquisition).
The others usual confocal imaging issues are being addressed by the microscope researchers, in hardware. There are actually building a new microscope which should (according to the first experiment) improve the contrast by a factor two at least, and reduce the usual problems.
One other solution is to improve the resolution. For that, are using a two-passes approach to improve the resolution without augmenting the acquisition time. Unfortunately, it leads to interlacing artifacts. We are working on a software solution to remove that too.
























Resources
![]() |
|
Download All |
Statistics more
![]() |
|
Global rating: | ![]() ![]() ![]() ![]() ![]() |
Review rating: | ![]() ![]() ![]() ![]() ![]() |
Code rating: | |
Paper Quality: |
![]() ![]() |
Information more
![]() |
|
Keywords: | system biology, Cell tracking, confocal imaging |
Export citation: |
Share
![]() |
Linked Publications more
![]() |
||
![]() by Vimort J., McCormick M., Paniagua B.
|
||
![]() by Beare R., Micevski D., Share C., Parkinson L., Ward P., Goscinski W., Kuiper M.
|
View license
Send a message to the author
