Trace vessels: User-guided tracing mode (3D)

Available with the Neurolucida 360 Ultra package only. Click here for more information.

Procedure overview

See Tracing vessels using user-guided mode (3D) for step-by-step instructions.

  • If you want to associate vessels with a specific color channel, select a single channel using either the Channel panel on the left side of the 3D environment window or the Image Adjustment tool (on the Image and Workspace ribbons) in the 2D window before you start.
  • To trace, click along a vessel, then right-click to end.

Vessel-tracing settings (user-guided mode)

Tracing options

  • Snap cursor to vessel: [Selected by default in User-guided mode]

  • Cycle vessel colors: A new color is used every time you start a new vessel.

  • Pan to window after each click: Each point you click that falls outside the field of view is re-centered automatically.

  • Display other vessels as centerline: Displays vessels that are already traced as lines (instead of showing thickness).

User-guided tracing options

  • Typical process width : This setting helps guide the algorithm during tracing and is especially helpful when there is a large range in vessel sizes. In this case, enter the typical width of the larger vessels.

  • Method: Choose one of the methods from the drop-down menu.

    • Directional Kernels: 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).

    • Rayburst Crawl: This method performs rayburst sampling measurements to obtain the diameter and centroid of the cross-section of the vessel. Successive measurements are used to position the nodes that define its centerline. Points are estimated until a set of stopping criteria is met.

      For details on the rayburst sampling algorithm see Rayburst sampling, an algorithm for automated three-dimensional shape analysis from laser scanning microscopy images (Rodriguez, Ehlenberger, Hof, & Wearne, 2006).

    • Voxel Scooping: 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. As in the other methods, points are estimated until a set of stopping criteria is met.

      For details on the algorithm, see Three-Dimensional Neuron Tracing by Voxel Scooping (Rodriguez, Ehlenberger, Hof, & Wearne, 2009).

    • CNN Sectioning: This algorithm builds on the Rayburst Crawl method by making use of a pre-trained Convolutional Neural Network (CNN) to dynamically segment the local image cross-section before performing each Rayburst Sampling measurement. This segmentation step makes it possible for the algorithm to correctly estimate the diameter and centroid of hollow vessels.

  • Place ending using right-click: By default, ends a vessel with a single right-click. If you uncheck this option, you'll see a menu with additional options when you right-click.