1. Tree Structure Extraction in Vascular Images Using Edge Detecting Trace Algorithms Marc Lockhart

2. Problem Description Given a set of vascular images, we wish
to extract the blood vessel network as a set
of tree structures.

3. Application Areas
Blood vessels are important image features used by clinicians and physicians for research and diagnostic purposes.

4. Vascular Extraction Methods
Conventional edge detection
Vessel tracing
Input Sobel Vessel Tracing

5. Vessel Tracing Algorithm Overview
Stage 1
Seed Selection: Identify points that are the most likely to be
located on a vessel. These are called seed points.
Stage 2
Tracing: Perform exploratory searches from each of the seed
points. Local image data that match the traits of blood
vessels are "traced".

6. Seed Point Selection Overview
The image is searched along a set of gridlines.
local intensity minima are selected as candidate seed points.
Candidate seed points are verified by the criteria:
The seed point must be between 2 parallel edges.
The seed point's response to the 2D edge detection kernel must exceed the threshold seedT.

7. The 2D Edge Detection Kernel
High responses to Kr and Kl indicate that a vessel edge has been detected. For this work, Kr and Kl are rotated through 16 directions to find the max responses. The direction at which the maximum occurs is stored as MaxDir.

8. Tracing Overview 1. Trace begins at p0 , i.e. the seed point.
2. At each point pk along the vessel, the next point must be
estimated.
pk+1= pk + α uk.
3. The unit vector points in the direction MaxDir,
as calculated by Kr and Kl.
4. Trace ends when the sum of the maximum Kr and Kl
responses does not exceed the threshold traceT.

9. Tracing Complexities Discontinuities in vessel segments
Intersections between vessels
Vessels in close proximity to each other
Branch points
Atypical background/foreground contrast
Contrast among foreground elements
Extreme curvatures
Boundaries not part of vasculature
Each complexity contributes to either undetected vessels/segments, or false detections.

10. Initial Results of Tracing Algorithm

11. Addressing the Contrast Problem (Final Results)
Observation: seedT and traceT are constants, and
cannot adapt to contrast information
gained during execution.
Strategy:
1. Initialize the thresholds seedT and traceT to high
values and execute the trace algorithm.
2. Dilate all traced vessels and recalculate seedT, traceT.
3. Repeat trace algorithm using updated thresholds.