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mdoube merged 1 commit into from
Jun 24, 2026
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Expose the topology-tagged image and the tree labelled image #424

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188 changes: 154 additions & 34 deletions Modern/wrapperPlugins/src/main/java/org/bonej/wrapperPlugins/AnalyseSkeletonWrapper.java
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Original file line number Diff line number Diff line change
Expand Up @@ -98,61 +98,167 @@ public class AnalyseSkeletonWrapper extends BoneJCommand {
LegacyInjector.preinit();
}

/** The binary 3D image to skeletonize and analyze. */
@Parameter(label = "Input image", validater = "validateImage",
persist = false)
private Dataset inputDataset;

/**
* Cycle pruning method for the skeleton graph.
* <ul>
* <li>"None" — no pruning</li>
* <li>"Shortest branch" — remove the shortest branch in each cycle</li>
* <li>"Lowest intensity voxel" — break cycle at the darkest voxel</li>
* <li>"Lowest intensity branch" — break cycle at the darkest branch</li>
* </ul>
* The latter two require an additional grayscale intensity image.
*/
@Parameter(label = "Cycle pruning method",
description = "Which method is used to prune cycles in the skeleton graph",
required = false, style = ChoiceWidget.LIST_BOX_STYLE, choices = { "None",
"Shortest branch", "Lowest intensity voxel", "Lowest intensity branch" })
private String pruneCycleMethod = "None";

/** If true, prune terminal branches (very short edges with no slab voxels). */
@Parameter(label = "Prune ends",
description = "Prune very short edges with no slabs", required = false)
private boolean pruneEnds;

/**
* If true, the current ROI is excluded from end-branch pruning.
* Voxels inside the ROI are spared even if they are end-points.
* Ignored in headless/batch mode.
*/
@Parameter(label = "Exclude ROI from pruning",
description = "Exclude the current selection from pruning",
required = false, visibility = ItemVisibility.INVISIBLE, persist = false)
private boolean excludeRoi;

/**
* If true, compute the longest shortest path (graph diameter) for each
* skeleton tree using the Floyd–Warshall algorithm.
* Populates the {@link #shortestPaths} output image and the
* "Longest Shortest Path" / "spx" / "spy" / "spz" columns in the results table.
*/
@Parameter(label = "Calculate largest shortest paths",
description = "Calculate and display the largest shortest skeleton paths",
required = false)
private boolean calculateShortestPaths;

/**
* If true, populate the {@link #verboseTable} with per-branch details
* (lengths, vertex coordinates, intensities, Euclidean distances).
*/
@Parameter(label = "Show detailed info",
description = "Show detailed branch info in an additional table",
required = false)
private boolean verbose;

@Parameter(label = "Display labelled skeletons",
description = "Show skeleton images labelled with their IDs",
/**
* If true, populate the {@link #taggedImage} and {@link #treeLabeledImage}
* output images. If false, both will be null (saving memory for batch jobs
* that only need numeric results).
*/
@Parameter(label = "Display skeleton images",
description = "Output topology-tagged and tree-labeled skeleton images",
required = false)
private boolean displaySkeletons;

/**
* Additional analysis details in a {@link DefaultGenericTable}, null if
* {@link #verbose} is false, or there are no results.
* Topology-tagged skeleton image (8-bit).
* <p>
* Each foreground voxel is labeled with its topological role in the
* skeleton graph:
* </p>
* <ul>
* <li>{@code 0} — background</li>
* <li>{@code 30} ({@link AnalyzeSkeleton_#END_POINT END_POINT}) —
* terminal endpoint (1 neighbor)</li>
* <li>{@code 70} ({@link AnalyzeSkeleton_#JUNCTION JUNCTION}) —
* junction vertex (3+ neighbors)</li>
* <li>{@code 127} ({@link AnalyzeSkeleton_#SLAB SLAB}) —
* slab voxel (exactly 2 neighbors)</li>
* </ul>
* <p>
* Source: {@code AnalyzeSkeleton_.getResultImage(false)} which returns
* the internal {@code taggedImage} stack.
* </p>
* <p>
* Null if {@link #displaySkeletons} is false.
* </p>
*/
@Parameter(type = ItemIO.OUTPUT, label = "Branch information")
private DefaultGenericTable verboseTable;
@Parameter(type = ItemIO.OUTPUT, label = "Tagged topology skeleton")
private Dataset taggedImage;

/**
* The labelled skeletons image, null if user didn't check the
* {@link #displaySkeletons} option.
* Tree-labeled skeleton image (float32).
* <p>
* Each foreground voxel is assigned the integer ID of the skeleton tree
* (connected component) it belongs to. Background is 0.
* </p>
* <ul>
* <li>{@code 0.0} — background</li>
* <li>{@code 1.0} — first skeleton tree</li>
* <li>{@code 2.0} — second skeleton tree</li>
* <li>{@code N.0} — N-th skeleton tree</li>
* </ul>
* <p>
* Stored as float32 (not uint8) because the number of distinct trees
* can exceed 255. Float can exactly represent integer IDs up to
* 2&#x2074;&#x00B2; without loss of precision.
* </p>
* <p>
* Source: {@code AnalyzeSkeleton_.getLabeledSkeletons()} which returns
* the internal {@code labeledSkeletons} stack.
* </p>
* <p>
* <b>Naming note:</b> This corresponds to the field called
* {@code labeledSkeletons} inside {@code AnalyzeSkeleton_}. It is
* <em>not</em> the same as the tagged image (confusingly, the original
* wrapper named its output {@code labelledSkeleton} but it actually held
* the tagged image). This field is now renamed to avoid that ambiguity.
* </p>
* <p>
* Null if {@link #displaySkeletons} is false.
* </p>
*/
@Parameter(type = ItemIO.OUTPUT)
private Dataset labelledSkeleton;
@Parameter(type = ItemIO.OUTPUT, label = "Tree-labeled skeleton")
private Dataset treeLabeledImage;

/**
* The shortest paths image, null if user didn't check the
* {@link #displaySkeletons} option.
* Longest-shortest-path image (8-bit).
* <p>
* A copy of the input skeleton stack where voxels lying on the
* longest shortest path (graph diameter) of each tree are overwritten
* with value {@code 96} ({@link AnalyzeSkeleton_#SHORTEST_PATH SHORTEST_PATH}).
* All other skeleton voxels retain their original intensity.
* </p>
* <p>
* Source: {@code AnalyzeSkeleton_.getResultImage(true)} which returns
* the internal {@code shortPathImage} stack.
* </p>
* <p>
* Null if {@link #calculateShortestPaths} is false.
* </p>
*/
@Parameter(type = ItemIO.OUTPUT)
@Parameter(type = ItemIO.OUTPUT, label = "Shortest paths")
private Dataset shortestPaths;

/**
* Per-branch detail table (only populated if {@link #verbose} is true).
* <p>
* Columns: {@code # Skeleton}, {@code # Branch}, {@code Branch length},
* {@code V1 x}, {@code V1 y}, {@code V1 z}, {@code V2 x}, {@code V2 y},
* {@code V2 z}, {@code Euclidean distance}, {@code running average length},
* {@code average intensity (inner 3rd)}, {@code average intensity}.
* </p>
* <p>
* Null if {@link #verbose} is false.
* </p>
*/
@Parameter(type = ItemIO.OUTPUT, label = "Branch information")
private DefaultGenericTable verboseTable;

@Parameter
private UIService uiService;

Expand All @@ -170,7 +276,7 @@ public class AnalyseSkeletonWrapper extends BoneJCommand {

@Parameter
private StatusService statusService;

@Parameter
private LegacyService legacyService;

Expand All @@ -187,12 +293,12 @@ public void run() {
}
}

ImagePlus imp = convertService.convert(inputDataset, ImagePlus.class);
if (imp == null) {
logService.error("Connectivity: Failed to convert Dataset to ImagePlus.");
return;
}
ImagePlus imp = convertService.convert(inputDataset, ImagePlus.class);
if (imp == null) {
logService.error("AnalyseSkeleton: Failed to convert Dataset to ImagePlus.");
return;
}

statusService.showStatus("Analyse skeleton: skeletonising");
final ImagePlus skeleton = skeletonise(imp);
Expand All @@ -211,32 +317,46 @@ public void run() {
}
showResults(results);
showAdditionalResults(results);

if (displaySkeletons) {
final ImageStack labelledStack = analyzeSkeleton_.getResultImage(false);
ImagePlus labelSkeleton = new ImagePlus(imp.getTitle() +
"-labelled-skeletons", labelledStack);
labelSkeleton.setCalibration(imp.getCalibration());
labelledSkeleton = convertService.convert(labelSkeleton, Dataset.class);
labelSkeleton.close();
labelledSkeleton.getImgPlus().setColorTable(ColorTables.FIRE, 0);
//if there is a UI, display the dataset
if (uiService != null && uiService.isVisible())
uiService.show(labelledSkeleton);
// --- Tree-labeled image (float32, IDs 1, 2, 3...) ---
final ImageStack treeLabeledStack = analyzeSkeleton_.getLabeledSkeletons();
if (treeLabeledStack != null) {
ImagePlus treeLabeledImp = new ImagePlus(imp.getTitle() +
"-tree-labels", treeLabeledStack);
treeLabeledImp.setCalibration(imp.getCalibration());
treeLabeledImage = convertService.convert(treeLabeledImp, Dataset.class);
treeLabeledImp.close();
treeLabeledImage.getImgPlus().setColorTable(ColorTables.FIRE, 0);
if (uiService != null && uiService.isVisible())
uiService.show(treeLabeledImage);
}

// --- Tagged topology image (8-bit, values 0, 30, 70, 127) ---
final ImageStack taggedStack = analyzeSkeleton_.getResultImage(false);
ImagePlus taggedSkeleton = new ImagePlus(imp.getTitle() +
"-tagged-skeletons", taggedStack);
taggedSkeleton.setCalibration(imp.getCalibration());
taggedImage = convertService.convert(taggedSkeleton, Dataset.class);
taggedSkeleton.close();
taggedImage.getImgPlus().setColorTable(ColorTables.FIRE, 0);
if (uiService != null && uiService.isVisible())
uiService.show(taggedImage);

if (calculateShortestPaths) {
// --- Shortest path image (8-bit, path voxels = 96) ---
final ImageStack stack = analyzeSkeleton_.getResultImage(true);
final String title = imp.getShortTitle() + "-shortest-paths";
ImagePlus shortPaths = new ImagePlus(title, stack);
shortPaths.setCalibration(imp.getCalibration());
shortestPaths = convertService.convert(shortPaths, Dataset.class);
shortPaths.close();
shortestPaths.getImgPlus().setColorTable(ColorTables.FIRE, 0);
//if there is a UI, display the dataset
if (uiService != null && uiService.isVisible())
uiService.show(shortestPaths);
if (uiService != null && uiService.isVisible())
uiService.show(shortestPaths);
}
}
}

private boolean hasNoSkeletons(final AnalyzeSkeleton_ analyzeSkeleton_) {
final Graph[] graphs = analyzeSkeleton_.getGraphs();
return graphs == null || graphs.length == 0;
Expand Down