Package sc.fiji.snt.tracing.auto
package sc.fiji.snt.tracing.auto
Automatic neuron tracing algorithms that reconstruct complete neuronal
morphologies from images without user interaction.
This package provides implementations of whole-neuron auto-tracing algorithms,
as opposed to the interactive point-to-point A*-based tracers in the parent
sc.fiji.snt.tracing package.
Key Classes
AutoTracer- Common interface for all auto-tracers, defining ROI strategy constants and thetraceTrees()contractAbstractAutoTracer- Base class for grayscale-based tracers with shared soma ROI handling and graph utilitiesGWDTTracer- APP2-style tracer using Gray-Weighted Distance Transform and hierarchical pruningBinaryTracer- Skeleton-based tracer using topological thinning and AnalyzeSkeleton
Algorithm Categories
- Grayscale-based (extends
AbstractAutoTracer) - Operate directly on intensity images without binarization. Use geodesic distance transforms and intensity-weighted path finding.
- Skeleton-based (
BinaryTracer) - Require binarization and topological skeletonization. Convert skeleton graphs to neuronal trees. Suitable for high-contrast images with clear foreground/background separation.
Soma ROI Strategies
All auto-tracers support configurable soma handling viaAutoTracer
constants:
ROI_UNSET- Ignore soma ROI, root at algorithm-specific pointROI_EDGE- Split into separate trees per neurite exiting somaROI_CENTROID- Collapse soma nodes to ROI geometric centroidROI_CENTROID_WEIGHTED- Collapse to weighted centroid of soma nodesROI_CONTAINED- Root on nodes inside ROI (skeleton-based only)
Usage Example
// Grayscale-based tracing
GWDTTracer<?> tracer = GWDTTracer.create(imagePlus);
tracer.setSeed(somaCenter);
tracer.setSomaRoi(somaRoi, AutoTracer.ROI_CENTROID);
List<Tree> trees = tracer.traceTrees();
// Skeleton-based tracing
BinaryTracer tracer = new BinaryTracer(binaryImage);
tracer.setRootRoi(somaRoi, AutoTracer.ROI_EDGE);
List<Tree> trees = tracer.traceTrees();
- Author:
- Tiago Ferreira
- See Also:
-
ClassDescriptionAbstract base class for grayscale-based automatic neuron tracers.AbstractGWDTTracer<T extends net.imglib2.type.numeric.RealType<T>>Abstract base class for GWDT-based tracers: APP2-style neuron tracer using Gray-Weighted Distance Transform and Fast Marching.Represents a hierarchical segment as defined by APP2.How the per-waypoint bias amount is derived.Derives
AbstractGWDTTracerconfiguration parameters from one or more example paths.Interface for automatic neuron tracers that reconstruct complete neuronal morphologies from images.Role aSeedPointplays in a tracing run.Class for generation ofTrees from a skeletonized image.ComponentReconnector<T extends net.imglib2.type.numeric.RealType<T>>Bridges gaps between disconnected components of an auto-traced neuron tree.DiskBackedGWDTTracer<T extends net.imglib2.type.numeric.RealType<T>>Disk-backed GWDT tracer for very large images.GWDTTracer<T extends net.imglib2.type.numeric.RealType<T>>In-memory GWDT tracer using array storage.Factory for creating optimal GWDT tracer implementations based on image size.Utilities for automatic soma detection and ROI generation.Container for soma detection results.SparseGWDTTracer<T extends net.imglib2.type.numeric.RealType<T>>Sparse GWDT tracer using hash map storage for memory efficiency.