1.0.0 Network Formation Assay Application Documentation
Application Name | Network Formation Assay |
Version | 1.0.0 |
Documentation Version | 10.10.2019 - 1 |
Input Image(s) | 2D (standard); RGB and grayscale (RGB images are automatically converted to grayscale images) |
Input Parameter(s) | None |
Keywords | network, tube, formation, in-vitro, angiogenesis, vessel, growth, microscopy, matrigel |
Short Description | Detection of branching points, loops, and cell coverage in network formation assay used for in-vitro angiogenesis research. |
References / Literature | For more information regarding the assay check e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3230200/; Reference laboratory: Department of Obstetrics and Gynecology: Dr. Ursula Hiden; Jasmin Strutz, MSc; |
Table of contents
IKOSA Prisma Network Formation Assay
You can use this image analysis application or any of our other applications in your account on the IKOSA platform. If it is not on the list of available applications, please contact your organization's administrator or our team at support@kmlvision.com.
Application description
This application automatically segments the network created by cells in a 2D network (tube) formation assay, typically on an extracellular matrix such as provided as the growth-factor reduced Matrigel® assay, and extracts relevant measures (loops, branching points, covered area).
In the following sections, we provide the necessary input data requirements that are necessary to obtain accurate image analysis results and a description of the output files.
Sample data
To try out this application, sample images can be downloaded here: https://drive.google.com/open?id=1WnUnZr4gbXp6-vpEvPfIa8yBgW_Ko3-P.
Input data requirements
Input image(s)
Input for this application is the following image data:
Image type | Color channels | Color depth (per channel) | Size (px) | Resolution (μm/px) |
|---|---|---|---|---|
2D (standard)
Check image format https://kmlvision.atlassian.net/wiki/spaces/KB/pages/3406725124 | 1 (Greyscale) 3 (RGB) RGB images are automatically converted to grayscale images | 8 Bit
| Min: 600 x 600 Max: 6832 x 5124 | typically: 1.75 |
Image content Microscopy image of 2D network (“tube”) formation assay, typically taken with 4x magnification. Additional requirements: None | ||||
Important:
For all images, the following requirements apply:
The illumination must be constant throughout the image(s).
The sample must be in focus, i.e. no blurry regions in image(s).
Input parameter(s)
No additional input parameters are required for this application.
Description of output files and their content
Files
File format | Description | |
|---|---|---|
| 1 | jpg | segmentation.jpg: An image with the same image dimensions as the input image, showing the segmentation of the tubes/cells. The image contains for each pixel a likelihood for being a tube. Values are in the range between 0 and 255. |
| 2 | csv | statistics.csv: A csv file containing statistics about input image. |
| 3 | csv | statistics_loops.csv: A csv file containing statistics about detected loops. |
| 4 | jpg | visualization.jpg: A visualization of the detection:
 |
Content
statistics.csv
Single csv-file
Column NO. | Column name | Examples | Value range | Description |
|---|---|---|---|---|
1 | branching points | 104 | 0 - | Number of detected branching points. |
2 | covered area | 93869 | 0 - #of pixels in image | Total area covered by cells or tubes in pixels. |
3 | num_tubes | 190 | 0 - | Number of Tubes detected. |
4 | total_tube_length | 6641.4 | 0 - #of pixels in image | Total length of all tubes in pixels. |
statistics_loops.csv
Single csv-file
Column NO. | Column name | Examples | Value range | Description |
|---|---|---|---|---|
1 | id | 1 | 1 - | Loop id. |
2 | area | 10747 | 0 - #of pixels in image | Area of the loop in pixels. |
3 | perimeter | 452.3 | 0 - | Perimeter of loop in pixels. |
Please note: The parameters marked with an asterisk (*) are calculated using https://scikit-image.org/.
Error information
More information about errors can be found in the Application Error Documentation.
Contact
If you have any questions about this app, as well as suggestions or ideas for new ones, email us at support@kmlvision.com.
Feel free to book a 30-minute meeting to speak with us about IKOSA and the apps!
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