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Rapid, Automated, and Robust Tracing of Vasculature, and Quantification of Visual Features from Angiographic Images

Published online by Cambridge University Press:  02 July 2020

Ali Can
Affiliation:
ECSE Department, Rensselaer Polytechnic Institute, Troy, NY12180-3590;
Hong Shen
Affiliation:
ECSE Department, Rensselaer Polytechnic Institute, Troy, NY12180-3590;
Khalid Al-Kofahi
Affiliation:
ECSE Department, Rensselaer Polytechnic Institute, Troy, NY12180-3590;
James N. Turner
Affiliation:
Wadsworth Center for Laboratories and Research, NYS-DOH, Albany, NY, 12201-0509;
Howard L. Tanenbaum
Affiliation:
The Center for Sight, 349 Northern Boulevard, Albany, NY, 12204;
Brian McCandless
Affiliation:
Albany Medical College, 47 New Scotland Ave., Albany, NY, 12208
Badrinath Roysam
Affiliation:
ECSE Department, Rensselaer Polytechnic Institute, Troy, NY12180-3590;
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Extract

The rapid tracing of vasculature, and quantification of visual landmarks such as those corresponding to the branching and crossover points from images is extremely useful in a variety of fields including ophthalmology, radiology, and neurobiology. A novel algorithm that enables rapid, automatic, robust, adaptive, and accurate tracing of vasculature has been developed. Given an image (Fig 1), it automatically generates a labeled graph representation of the vasculature (Fig 2), and a table listing the locations of visual landmarks such as crossover and branching points (Fig 3). For each such point, it also lists the intersection angles, and the local thickness of the intersecting vasculature segments. This data is often useful by itself. They can also be used for image registration and montage building.

This algorithm greatly improves upon previous work in several ways. First, it is fully automatic, and free of parameters that need to be adjusted carefully (just needs optional sensitivity setting).

Type
From Scanning Probe Microscopy to High Resolution Ultrasound: New Versions of the Vasculature
Copyright
Copyright © Microscopy Society of America 1997

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References

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4. Supported by National Science Foundation grants MIP-9412500, and MIP-9634206.Google Scholar