See Tracing with the automatic mode(3D)
To see the full panel, click Show Settings.
With this method, four directional kernels are matched to the image data. For a given point within the vessel, the algorithm identifies the best positions and orientations for the top, bottom, left, and right kernels surrounding the point. The positions and orientations results are combined to estimate the next point to trace. Points are estimated until a set of stopping criteria is met.
For details on the algorithm, see Rapid automated three-dimensional tracing of neurons from confocal image stacks (Al-Kofahi, Lasek, Szarowski, Pace, Nagy, Turner, and Roysam, 2002).
The detection is implemented from a branch centerline to its outer edges (manuscript in preparation).
This algorithm generates clusters of voxels iteratively along the vessel. These clusters are then used to position the nodes that define the centerline of the vessel.
For details on the algorithm, see Three-Dimensional Neuron Tracing by Voxel Scooping (Rodriguez, Ehlenberger, Hof, & Wearne, 2009).
Settings
Display Seeds
Click the Display seeds button to get a sense of how sensitivity and density are implemented.
Use the slider to adjust the sensitivity (%) for dim and low-contrast structures.
The program applies an invisible grid to sample the image uniformly.
Refine Seeds
The program examines the possible seed points' secondary characteristics to determine whether they are likely to belong to a branch.
The value indicates the quality of the match between seeds and branches. To change it, use the slider.
To change the color of manually added seeds, use the color picker.
Trace
Use the slider or type a value to adjust sensitivity to dim and low-contrast structures.
Maximum distance between two segments to make a connection. If the distance is greater than the gap value, the program doesn't connect the segments.