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Vessel branch segmentation

version 1.0.0.0 (19.9 KB) by Hiroshi Kawaguchi
Segment the vessel branches from dynamic image of fluorescent microscopy

2.3K Downloads

Updated 5 Apr 2012

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Segment the blood vessels from a dynamic image of fluorescent microscopy.

== Install ======

- Add all attached files to matlab path

- Download "Better Skeletonization" from following URL and add to matlab path
http://www.mathworks.com/matlabcentral/fileexchange/11123-better-skeletonization

== Instruction =========
1. Save time lapse images by tiff format in a directory.
The alphabetical order of file name must correspond to the order of time frame.

2. Read Tiff format files in a directory and save it in a matlab file.
>> imgData = VBSreadTiff('directory name');
Here, "imgData" is a structure of x,y,t image and the header of tiff.

3. Lounch VesselBranchSegmentation
>> VesselBranchSegmentation

4. In Menu, Select "File > New", then select a saved matfile.

5. In Menu, Select "Estimation > Vessel Mask", then vessel region is extracted from vessels.(*)

6. In Menu, Select "Estimation > Vessel Class", then vessel region is classified into artery and vein.(*)
This process takes a bit long time (~ 1 hour).

7. In Menu, Select "Estimation > Segmentation to Branches".
New window appears and skeleton of artery mask is calculated. (**)
Then press "To branch" button for segmentation to vessel branches.
After closing the skeleton-shown window, repeat the same process for vein region.

(*) The extracted mask can be modified by the edit tool.
Turn "Editable checkbox" on to use the edit tool.
See the document of impoly function for details.

(**) The undesired skeleton will be calculated for low SNR images because of the ambiguous edge of vessel.
The skeleton can be manually modified by the edit tool in the window.

Cite As

Hiroshi Kawaguchi (2022). Vessel branch segmentation (https://www.mathworks.com/matlabcentral/fileexchange/36031-vessel-branch-segmentation), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired by: Better Skeletonization

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