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Vessel Detection Executable

Download Command-Line Executable

This executable will process the image pixel-by-pixel to apply the Likelihood Ratio Vesselness (LRV) image wide. It is therefore slower than the vessel tracing executable.

Platform Training Data Used
Windows (08/13/2007) STARE and DRIVE* STARE DRIVE
FreeBSD (08/13/2007 static build on FreeBSD 5.4) STARE and DRIVE* STARE DRIVE
Linux (08/13/2007 static build on kernel 2.6) STARE and DRIVE* STARE DRIVE
* Training using STARE data set and DRIVE data set (with manual segmentations by observer 1). Use this version for best results.


The executable has only one argument, which is the image file to process.

This executable can be used for non-commercial purposes only.


Four files are written for each run: 1) Likelihood Ratio Vesselness at each pixel of the input image (header+content), 2) Vessel matched filter computed at each pixel of the input image (header+content). Each of these outputs is in the Insight Toolkit RAW format, because they are floating point outputs. Extension .mhd specifies the file header and extension .raw is the image content. Do not linearly scale the output of the LRV filter before use (i.e. by stretching to <0, 255> interval of integer intensities) because it is a likelihood ratio and you will loose important responses (many would get rounded to zero).

If you work in MATLAB, you can use the following function to read the raw images: readRaw.m
Example Usage:

readRaw( 'C:\path_to_image\imagefile.raw', [ImageWidth ImageHeight], 'float', 'native', 0 );

Note: You need to specify the image size ([ImageWidth ImageHeight]) manually. This can be determined from the header file (.mhd file).

Publications and Further Reading

When you publish results using the executable, please acknowledge the authors by citing the following paper:

Retinal Vessel Centerline Extraction Using Multiscale Matched Filters, Confidence and Edge Measures
Michal Sofka and Charles V. Stewart
IEEE Transactions on Medical Imaging, vol. 25, no. 12, pp. 1531-1546, Dec. 2006.
[pdf with erratum] [bibtex]

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For questions and comments contact Michal Sofka at:


Copyright 2017 Michal Sofka