{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#  T07: Curvature Optimization with Automated Path Tracing\n",
"\n",
"\n",
"## Overview\n",
"\n",
"This tutorial demonstrates how to use PySNT's A* path tracing capabilities to optimize neuronal reconstructions by re-tracing along waypoints through the original image data. This workflow is useful for:\n",
"\n",
"- **Refining coarse reconstructions** obtained from automated segmentation pipelines\n",
"- **Improving manual tracings** by snapping paths to the underlying fluorescence signal\n",
"- **Assigning thickness** to skeletonized tracings lacking radius information\n",
"- **Generating high-fidelity ground truth** for training segmentation algorithms\n",
"\n",
"\n",
"```{admonition} Learning Objectives\n",
":class: tip\n",
"\n",
"By the end of this tutorial, you will be able to:\n",
"1. Perform headless A* auto-tracing between waypoints in fluorescent imagery\n",
"2. Programmatically optimize path trajectories to follow intensity ridges\n",
"3. Fit cross-sectional profiles to estimate neurite thickness\n",
"4. Quantitatively compare original and optimized reconstructions\n",
"\n",
"**Estimated Time**: 45 minutes\n",
"```\n",
"\n",
"```{note}\n",
"Make sure to read these resources before running this notebook:\n",
"- [Install](../install.md) - Installation instructions\n",
"- [Tutorial 01](./01_single_cell_analysis.ipynb) - Single cell analysis basics\n",
"- [Tutorial 05](./05_napari_viewer.ipynb) - Working with images and reconstructions\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Introduction\n",
"\n",
"Neuronal reconstructions vary widely in detail and accuracy. Coarse reconstructions may capture overall topology but lack the fine curvature that follows actual neurite fluorescence. Conversely, we may want to validate whether an existing reconstruction faithfully follows the image signal. This tutorial demonstrates how to programmatically optimize path curvatures using A* search, an algorithm that finds optimal paths by balancing distance traveled against image intensity (aka _cost function_), ensuring traces follow actual neurite fluorescence. SNT provides several A* variants and cost functions; for simplicity, we will stick to the defaults here.\n",
"\n",
"**Tutorial Rationale:**\n",
"\n",
"We will validate the A* optimization workflow by:\n",
"\n",
"1. **Degrading** a gold-standard reconstruction to a barebones minimum composed only of branch points and end points\n",
"2. **Retracing** paths between these anchor points using A* search through the original image\n",
"3. **Comparing** the retraced structure against the original to assess recovery of path curvatures\n",
"\n",
"As ground truth, we use the **OP_1** dataset from the [DIADEM challenge](https://diadem.janelia.org/), previously introduced in [Tutorial 05](./05_napari_viewer.ipynb)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Setup and Initialization\n",
"\n",
"As always, we start by initializing pysnt with appropriate settings for notebook execution:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pysnt\n",
"pysnt.set_option('java.logging.level', 'Error')\n",
"pysnt.set_option('display.chart_format', 'svg')\n",
"pysnt.set_option('display.chart_dpi', 150)\n",
"pysnt.initialize()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We'll also need numpy for numerical operations and matplotlib for visualization:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Loading Data\n",
"Here we will use the *OP_1* demo dataset already used in [Tutorial 05](./05_napari_viewer.ipynb). We'll load both the reconstruction ({class}`pysnt.Tree`) and the source image using {class}`pysnt.SNTService`, as we have been doing since [Tutorial 01](./01_single_cell_analysis.ipynb):"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tree: Original\n",
" No. of nodes: 1544\n",
" No. of branch points: 48\n",
" No. of tips: 49\n",
" Cable length: 746.40 µm\n"
]
}
],
"source": [
"from pysnt import SNTService\n",
"\n",
"snt_service = SNTService()\n",
"\n",
"# Load the ground-truth reconstruction\n",
"original_tree = snt_service.demoTree('OP1')\n",
"original_tree.setLabel('Original')\n",
"\n",
"def print_info(tree):\n",
" from pysnt.analysis import TreeStatistics\n",
" print(f\"Tree: {tree.getLabel()}\")\n",
" print(f\" No. of nodes: {tree.getNodes().size()}\")\n",
" stats = TreeStatistics(tree)\n",
" print(f\" No. of branch points: {stats.getBranchPoints().size()}\")\n",
" print(f\" No. of tips: {stats.getTips().size()}\")\n",
" print(f\" Cable length: {stats.getCableLength():.2f} µm\")\n",
"\n",
"print_info(original_tree)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Image: OP_1.tif\n",
" Dimensions: 512 x 512 x 60\n",
" Voxel size: 0.32964852215271034 x 0.32964852215271034 x 0.9988 microns\n"
]
}
],
"source": [
"# Load the source image\n",
"img = snt_service.demoImage('OP1') # ImagePlus object\n",
"\n",
"# Display some basic properties\n",
"print(f\"Image: {img.getTitle()}\")\n",
"print(f\" Dimensions: {img.getWidth()} x {img.getHeight()} x {img.getNSlices()}\")\n",
"cal = img.getCalibration()\n",
"print(f\" Voxel size: {cal.pixelWidth} x {cal.pixelHeight} x {cal.pixelDepth} {cal.getUnit()}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's visualize the image its ground truth reconstruction:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Obtaining Waypoints\n",
"\n",
"To degrade the gold standard Tree we can use the `downsample()` method with a large internode spacing. Because branch points and endpoints are always preserved during downsampling, setting a very large spacing (e.g., 1 mm) effectively reduces the tree to just these critical points:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# Create a copy of the tree for simplification\n",
"degraded_tree = original_tree.clone()\n",
"degraded_tree.setLabel(\"Degraded Tree\")\n",
"\n",
"# Downsample with large spacing to retain only branch points and tips\n",
"# Branch points and end points are always preserved\n",
"degraded_tree.downsample(1000.0) # 1000 µm spacing"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's visualize the simplified structure alongside the original:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tree: Degraded Tree\n",
" No. of nodes: 146\n",
" No. of branch points: 48\n",
" No. of tips: 49\n",
" Cable length: 669.05 µm\n"
]
},
{
"data": {
"text/plain": [
"{'type': matplotlib.figure.Figure,\n",
" 'data': ,\n",
" 'metadata': {'source_type': 'SNTChart_List',\n",
" 'sntchart_count': 2,\n",
" 'displayed_count': 2,\n",
" 'panel_layout': 'auto',\n",
" 'title': None},\n",
" 'error': None}"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Create side-by-side comparison\n",
"print_info(degraded_tree)\n",
"degraded_tree.setLabel(\"Degraded (Branch Points + Tips)\")\n",
"pysnt.display([original_tree, degraded_tree], show_panel_titles=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A* Tracing Between Waypoints\n",
"\n",
"Now we use SNT's A* search to find optimal paths between consecutive anchor points through the image. The {class}`pysnt.SNT` class provides access to the tracing engine:\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tree: Degraded (Branch Points + Tips)\n",
" No. of nodes: 146\n",
" No. of branch points: 48\n",
" No. of tips: 49\n",
" Cable length: 669.05 µm\n"
]
},
{
"data": {
"text/plain": [
"{'type': matplotlib.figure.Figure,\n",
" 'data': ,\n",
" 'metadata': {'source_type': 'SNTChart_List',\n",
" 'sntchart_count': 3,\n",
" 'displayed_count': 3,\n",
" 'panel_layout': (1, 3),\n",
" 'title': None},\n",
" 'error': None}"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def trace_between_anchors(img, simplified_tree):\n",
" \"\"\"\n",
" Re-trace paths between waypoints using A* search.\n",
"\n",
" Parameters\n",
" ----------\n",
" img : ImagePlus or ImgPlus\n",
" Image to be traced\n",
" simplified_tree : Tree\n",
" Tree containing waypoints\n",
"\n",
" Returns\n",
" -------\n",
" Tree\n",
" New tree with paths traced through the image\n",
" \"\"\"\n",
" from pysnt import Tree, SNT\n",
" snt = SNT(img)\n",
" traced_tree = simplified_tree.clone()\n",
" for path in traced_tree.list():\n",
" nodes = path.getNodes()\n",
" # This autoTrace call uses 3 arguments: list of waypoints,\n",
" # branch point to a parent path (not used here), and\n",
" # boolean flag for headless execution\n",
" traced_path = snt.autoTrace(nodes, None, True)\n",
" if traced_path is not None:\n",
" path.replaceNodes(traced_path) # Replace nodes (fork points automatically adjusted)\n",
"\n",
" return traced_tree\n",
"\n",
"\n",
"traced_tree = trace_between_anchors(img, degraded_tree)\n",
"traced_tree.setLabel(\"A* Tree\")\n",
"print_info(degraded_tree)\n",
"pysnt.display([original_tree, degraded_tree, traced_tree], panel_layout=(1,3), show_panel_titles=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can overlay both reconstructions to better gauge their spatial overlap:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"{'type': matplotlib.figure.Figure,\n",
" 'data': ,\n",
" 'metadata': {'source_type': 'SNTChart',\n",
" 'format': 'svg',\n",
" 'scale': 1.0,\n",
" 'is_combined': False,\n",
" 'title': 'Reconstruction Plotter',\n",
" 'containsValidData': True,\n",
" 'isLegendVisible': True},\n",
" 'error': None}"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Overlay visualization with different colors\n",
"def overlay_trees(tree1, tree2):\n",
" \"\"\"Overlay two trees with different colors.\"\"\"\n",
" from pysnt.viewer import Viewer2D\n",
" viewer = Viewer2D()\n",
" tree1.setColor(\"blue\")\n",
" viewer.add(tree1)\n",
" tree2.setColor(\"red\")\n",
" viewer.add(tree2)\n",
" title = f\"{tree1.getLabel()} (blue) vs {tree2.getLabel()} (red)\"\n",
" return pysnt.display(viewer, title = title)\n",
"\n",
"overlay_trees(original_tree, traced_tree)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Evaluation\n",
"\n",
"To assess how well the retraced structure matches the original, we'll compute several similarity metrics to help us understand the spatial overlap and geometric similarity between the two trees. We will use [SciPy](https://scipy.org/) to compute:\n",
"\n",
"1. **Jaccard Similarity**: Measures the overlap between two sets of points as the ratio of intersection to union\n",
"2. **Hausdorff Distance**: The maximum distance from any point in one set to the nearest point in the other set\n",
"3. **Cable Length Ratio**: Comparison of total cable lengths"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"from scipy.spatial.distance import directed_hausdorff\n",
"from scipy.spatial import cKDTree\n",
"\n",
"def compute_jaccard_similarity(points1, points2, tolerance=1.0):\n",
" \"\"\"\n",
" Compute Jaccard similarity between two point clouds.\n",
" \n",
" Points are considered overlapping if they are within the specified tolerance.\n",
" \n",
" Parameters\n",
" ----------\n",
" points1 : np.ndarray\n",
" First point cloud (N, 3)\n",
" points2 : np.ndarray\n",
" Second point cloud (M, 3)\n",
" tolerance : float\n",
" Distance threshold for considering points as overlapping\n",
" \n",
" Returns\n",
" -------\n",
" float\n",
" Jaccard similarity coefficient (0 to 1)\n",
" \"\"\"\n",
" # Build KD-trees for efficient nearest neighbor queries\n",
" tree1 = cKDTree(points1)\n",
" tree2 = cKDTree(points2)\n",
" \n",
" # Find points in set1 that have a neighbor in set2 within tolerance\n",
" distances1, _ = tree2.query(points1)\n",
" overlap1 = np.sum(distances1 <= tolerance)\n",
" \n",
" # Find points in set2 that have a neighbor in set1 within tolerance\n",
" distances2, _ = tree1.query(points2)\n",
" overlap2 = np.sum(distances2 <= tolerance)\n",
" \n",
" # Jaccard: intersection / union\n",
" # Intersection approximated as average of bidirectional overlaps\n",
" intersection = (overlap1 + overlap2) / 2\n",
" union = len(points1) + len(points2) - intersection\n",
" \n",
" return intersection / union if union > 0 else 0.0\n",
"\n",
"\n",
"def compute_hausdorff_distance(points1, points2):\n",
" \"\"\"\n",
" Compute bidirectional Hausdorff distance between two point clouds.\n",
" \n",
" Parameters\n",
" ----------\n",
" points1 : np.ndarray\n",
" First point cloud (N, 3)\n",
" points2 : np.ndarray\n",
" Second point cloud (M, 3)\n",
" \n",
" Returns\n",
" -------\n",
" float\n",
" Hausdorff distance (maximum of both directed distances)\n",
" \"\"\"\n",
" d1 = directed_hausdorff(points1, points2)[0]\n",
" d2 = directed_hausdorff(points2, points1)[0]\n",
" return max(d1, d2)\n",
"\n",
"\n",
"def compute_overlap_coefficient(points1, points2, tolerance=1.0):\n",
" \"\"\"\n",
" Compute overlap coefficient (Szymkiewicz-Simpson) between two point clouds.\n",
" \n",
" The overlap coefficient is the size of intersection divided by the \n",
" size of the smaller set, ranging from 0 (no overlap) to 1 (smaller \n",
" set completely contained in larger).\n",
" \n",
" Parameters\n",
" ----------\n",
" points1 : np.ndarray\n",
" First point cloud (N, 3)\n",
" points2 : np.ndarray\n",
" Second point cloud (M, 3)\n",
" tolerance : float\n",
" Distance threshold for considering points as overlapping\n",
" \n",
" Returns\n",
" -------\n",
" float\n",
" Overlap coefficient (0 to 1)\n",
" \"\"\"\n",
" tree2 = cKDTree(points2)\n",
" distances, _ = tree2.query(points1)\n",
" intersection = np.sum(distances <= tolerance)\n",
" \n",
" min_size = min(len(points1), len(points2))\n",
" return intersection / min_size if min_size > 0 else 0.0\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now let's compute these metrics comparing the original tree to the traced result:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Comparison Report:\n",
" Original tree: 1544 points\n",
" Traced tree: 1661 points\n",
"\n",
"Similarity Metrics (tolerance=1.0 µm):\n",
" Jaccard Similarity: 0.9123\n",
" Hausdorff Distance: 3.66 µm\n",
" Overlap Coefficient: 0.9482\n",
"\n",
"Cable Length Comparison:\n",
" Original: 746.40 µm\n",
" Traced: 844.01 µm\n",
" Ratio (traced/original): 1.1308\n"
]
}
],
"source": [
"\n",
"\n",
"def comparison_report(original_tree, traced_tree):\n",
" \"\"\"Display comparison values between original and traced tree\"\"\"\n",
" from pysnt.analysis import TreeStatistics\n",
"\n",
" print(f\"Comparison Report:\")\n",
"\n",
" # Extract point clouds: Extract node coordinates from Trees as numpy arrays\n",
" original_points = pysnt.tree_to_points(original_tree)\n",
" traced_points = pysnt.tree_to_points(traced_tree)\n",
" \n",
" # No. of nodes\n",
" print(f\" Original tree: {len(original_points)} points\")\n",
" print(f\" Traced tree: {len(traced_points)} points\")\n",
"\n",
" # Compute similarity metrics\n",
" tolerance = 1.0 # µm, based on voxel size\n",
" jaccard = compute_jaccard_similarity(original_points, traced_points, tolerance=tolerance)\n",
" hausdorff = compute_hausdorff_distance(original_points, traced_points)\n",
" overlap = compute_overlap_coefficient(original_points, traced_points, tolerance=tolerance)\n",
" print(f\"\\nSimilarity Metrics (tolerance={tolerance} µm):\")\n",
" print(f\" Jaccard Similarity: {jaccard:.4f}\")\n",
" print(f\" Hausdorff Distance: {hausdorff:.2f} µm\")\n",
" print(f\" Overlap Coefficient: {overlap:.4f}\")\n",
"\n",
" # Compare cable lengths using TreeStatistics\n",
" stats_original = TreeStatistics(original_tree)\n",
" stats_traced = TreeStatistics(traced_tree)\n",
" cable_original = stats_original.getCableLength()\n",
" cable_traced = stats_traced.getCableLength()\n",
" print(f\"\\nCable Length Comparison:\")\n",
" print(f\" Original: {cable_original:.2f} µm\")\n",
" print(f\" Traced: {cable_traced:.2f} µm\")\n",
" print(f\" Ratio (traced/original): {cable_traced/cable_original:.4f}\")\n",
"\n",
"comparison_report(original_tree, traced_tree)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Refinement: Fitting to Signal\n",
"\n",
"A* tracing recovers path topology, but node positions follow intensity ridges at voxel resolution. We can further refine the reconstruction by fitting cross-sectional intensity profiles perpendicular to each path tangent. This fitting procedure:\n",
"\n",
"1. **Samples circular cross-sections** around each node, oriented normal to the local path direction\n",
"2. **Optimizes center position** by finding the intensity centroid within the cross-section\n",
"3. **Estimates node radius** by fitting a circle to the intensity profile\n",
"\n",
"The [process](https://imagej.net/plugins/snt/manual#refinefit-) is multi-threaded, allowing paths to be fitted in parallel for efficient batch processing. Additionally, since fitting operates on a per-path basis, different paths can be fitted with different parameters if needed. "
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": []
}
],
"source": [
"from typing import Union\n",
"\n",
"def fit_tree(img: Union['ImagePlus', 'ImgPlus'], \n",
" tree: 'Tree', \n",
" search_radius: float = 2, \n",
" workers: int = 4) -> 'Tree':\n",
" \"\"\"\n",
" Fits circular cross-sections around path nodes to compute radii and refine centerline\n",
" coordinates.\n",
" \n",
" Performs PathFitter operations on all paths in a tree using parallel processing.\n",
" The fitting algorithm optimizes node positions and estimates node radii by \n",
" analyzing cross-sectional intensity profiles perpendicular to each path segment.\n",
" \n",
" Thread Safety:\n",
" The fitting process is divided into two phases to maintain tree hierarchy:\n",
" 1. Parallel computation phase: Each path is fitted independently without modifying \n",
" the original path geometry (thread-safe)\n",
" 2. Sequential application phase: Fitted results are applied to paths one-by-one \n",
" to preserve parent-child relationships and branch point indices\n",
" \n",
" Parameters\n",
" ----------\n",
" img : ImagePlus or ImgPlus\n",
" Should be a 2D or 3D image with the neuronal structure visible as bright \n",
" signal on dark background.\n",
" tree : Tree\n",
" The Tree object containing paths to be fitted. All paths in the tree will be \n",
" processed.\n",
" search_radius : float, optional\n",
" Maximum search radius in physical units for the fitting optimization. Defines \n",
" the neighborhood around each node where the algorithm searches for the optimal \n",
" cross-section. Default: 2 (µm)\n",
" workers : int, optional\n",
" Number of parallel worker threads for fitting. Default: 4.\n",
" \n",
" Returns\n",
" -------\n",
" Tree\n",
" The input tree with all paths fitted in place (refined XYZ coordinates and\n",
" estimated radius at each node (if successful)\n",
" \n",
" Notes\n",
" -----\n",
" Fitting Scope:\n",
" - RADII_AND_MIDPOINTS: Both node positions and radii are optimized\n",
" - Positions are refined by finding intensity-weighted centroids in cross-sections\n",
" - Radii are estimated by fitting circles to intensity gradients in cross-sections\n",
" \n",
" Fallback Strategy:\n",
" - FALLBACK_MODE: When fitting fails at a node, uses the mode (most common) \n",
" radius from nearby successful fits\n",
" - Alternative strategies: FALLBACK_MIN_SEP (use voxel size) or FALLBACK_NAN\n",
" \"\"\"\n",
" from pysnt import PathFitter\n",
" from concurrent.futures import ThreadPoolExecutor\n",
" \n",
" def fit_path(path):\n",
" \"\"\"Configure and compute fit for a single path (thread-safe).\"\"\"\n",
" fitter = PathFitter(img, path)\n",
" \n",
" # Fit both XYZ coordinates and radii using cross-sectional intensity analysis\n",
" fitter.setScope(PathFitter.RADII_AND_MIDPOINTS) \n",
" \n",
" # Constrain optimization to max_radius pixels around each node to:\n",
" # 1) improve performance by limiting search space; and 2) avoid finding\n",
" # spurious features far from the path\n",
" fitter.setCrossSectionRadius(search_radius)\n",
" \n",
" # When optimization fails (e.g., low SNR, ambiguous geometry), use the mode\n",
" # (most frequent) radius from nearby successful fits as a fallback\n",
" fitter.setNodeRadiusFallback(PathFitter.FALLBACK_MODE)\n",
"\n",
" # Critical for thread safety: Execute fitting algorithm without modifying path\n",
" # Replacing nodes modifies parent paths' geometry, which breaks branch point\n",
" # indices for children being fitted simultaneously during parallel execution.\n",
" # All fits will be applied sequentially _after_ parallel computation completes\n",
" fitter.call() # returns a ref. to fitted path\n",
" \n",
" return fitter\n",
"\n",
" # Step 1: Parallel fitting (computation only, without modifying paths)\n",
" with ThreadPoolExecutor(max_workers=workers) as executor:\n",
" fitters = list(executor.map(fit_path, tree.list()))\n",
" \n",
" # Step 2: Sequential application (maintains tree hierarchy integrity)\n",
" # Each applyFit() may update parent path geometry, so children's branch point\n",
" # indices must be recalculated. Sequential execution ensures parent geometry\n",
" # is finalized before children's branch points are updated.\n",
" for fitter in fitters:\n",
" fitter.setReplaceNodes(True) # in-place fit\n",
" fitter.applyFit()\n",
" \n",
" return tree\n",
"\n",
"\n",
"# Runt fits on a traced_tree copy, setting the search radius to 1.5um\n",
"fitted_tree = fit_tree(img, traced_tree.clone(), search_radius=1.5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's update the comparison report:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Comparison Report:\n",
" Original tree: 1544 points\n",
" Traced tree: 1167 points\n",
"\n",
"Similarity Metrics (tolerance=1.0 µm):\n",
" Jaccard Similarity: 0.9166\n",
" Hausdorff Distance: 3.78 µm\n",
" Overlap Coefficient: 1.2528\n",
"\n",
"Cable Length Comparison:\n",
" Original: 746.40 µm\n",
" Traced: 865.40 µm\n",
" Ratio (traced/original): 1.1594\n"
]
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"{'type': matplotlib.figure.Figure,\n",
" 'data': ,\n",
" 'metadata': {'source_type': 'SNTChart',\n",
" 'format': 'svg',\n",
" 'scale': 1.0,\n",
" 'is_combined': False,\n",
" 'title': 'Reconstruction Plotter',\n",
" 'containsValidData': True,\n",
" 'isLegendVisible': True},\n",
" 'error': None}"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"comparison_report(original_tree, fitted_tree)\n",
"overlay_trees(original_tree, fitted_tree)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Path fitting yields a more efficient representation with improved spatial agreement.\n",
"\n",
"The Jaccard similarity index increased, indicating better overlap despite fewer nodes. The slight increase in Hausdorff distance is not unexpected, as midpoint refinement can shift individual nodes toward local intensity maxima, occasionally increasing the maximum deviation at specific locations. The increased cable length ratio suggests that fitted paths may capture more faithfully fine curvatures that were previously approximated by straight segments between nodes.\n",
"\n",
"Let's examine how the Jaccard similarity varies with different tolerance values:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Compute Jaccard for range of tolerances\n",
"tolerances = np.linspace(0.3, 10.0, 20)\n",
"original_points = pysnt.tree_to_points(original_tree)\n",
"traced_points = pysnt.tree_to_points(fitted_tree)\n",
"\n",
"jaccards = [compute_jaccard_similarity(original_points, traced_points, t) for t in tolerances]\n",
"\n",
"fig, ax = plt.subplots(figsize=(8, 5))\n",
"ax.plot(tolerances, jaccards, 'b-o', linewidth=2, markersize=6)\n",
"ax.set_xlabel('Tolerance (µm)', fontsize=12)\n",
"ax.set_ylabel('Jaccard Similarity', fontsize=12)\n",
"ax.set_title('Jaccard Similarity vs. Tolerance Threshold', fontsize=14)\n",
"ax.grid(True, alpha=0.3)\n",
"ax.set_ylim([0, 1])\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The graph shows the Jaccard similarity between the original and retraced trees as a function of the spatial tolerance threshold. At very tight tolerances (0.5 µm), similarity is approximately 0.5, indicating that only half of the points align within sub-micron precision. Similarity increases rapidly between 0.5–2 µm, reaching ~0.97 at 1.5 µm, which corresponds roughly to the voxel size of the source image. Beyond 2 µm, similarity plateaus near 1.0, indicating that virtually all traced points lie within 2 µm of their corresponding original points. This steep initial rise followed by saturation suggests the retraced structure closely follows the original reconstruction, with deviations primarily at the sub-voxel scale—consistent with the expected precision of image-based path optimization.\n",
"\n",
"We can also visualize the point-to-point distances between the original and retraced structures:"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def plot_comparison_metrics(original_points, traced_points, \n",
" original_radii=None, traced_radii=None,\n",
" plot_distances=True, plot_radii=True):\n",
" \"\"\"\n",
" Plots spatial and/or radii comparisons between original and traced reconstructions.\n",
" \n",
" Parameters\n",
" ----------\n",
" original_points : ndarray\n",
" Original tree coordinates (N × 3). If None, distance plots are skipped.\n",
" traced_points : ndarray\n",
" Traced tree coordinates (M × 3)\n",
" original_radii : ndarray, optional\n",
" Original node radii (N,). If None, radii plots are skipped.\n",
" traced_radii : ndarray, optional\n",
" Traced node radii (M,). If None, radii plots are skipped.\n",
" plot_distances : bool, optional\n",
" If True, plot spatial distance metrics. Default: True\n",
" plot_radii : bool, optional\n",
" If True, plot radius difference metrics (requires radii arrays). Default: True\n",
" \n",
" Returns\n",
" -------\n",
" fig : matplotlib.figure.Figure\n",
" \"\"\"\n",
" # Determine what to plot\n",
" can_plot_distances = (original_points is not None and traced_points is not None)\n",
" can_plot_radii = (original_radii is not None and traced_radii is not None)\n",
" \n",
" if not can_plot_distances and not can_plot_radii:\n",
" raise ValueError(\"Must plot at least distances or radii\")\n",
" \n",
" # Determine layout\n",
" if can_plot_distances and can_plot_radii:\n",
" fig, axes = plt.subplots(2, 2, figsize=(14, 10))\n",
" metrics = [\n",
" (cKDTree(traced_points).query(original_points)[0], \n",
" 'Distance to Traced Point', 'steelblue', 'Spatial Distances'),\n",
" (np.abs(original_radii[:n] - traced_radii[:n]) if (n := min(len(original_radii), len(traced_radii))) else [],\n",
" 'Radius Difference', 'coral', 'Radius Differences')\n",
" ]\n",
" elif can_plot_distances:\n",
" fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n",
" axes = axes.reshape(1, 2) # Make 2D for consistent indexing\n",
" metrics = [(cKDTree(traced_points).query(original_points)[0], \n",
" 'Distance to Traced Point', 'steelblue', 'Spatial Distances')]\n",
" else: # only radii\n",
" fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n",
" axes = axes.reshape(1, 2)\n",
" n = min(len(original_radii), len(traced_radii))\n",
" metrics = [(np.abs(original_radii[:n] - traced_radii[:n]),\n",
" 'Radius Difference', 'coral', 'Radius Differences')]\n",
" \n",
" # Plot all metrics\n",
" for i, (data, label, color, title) in enumerate(metrics):\n",
" # Histogram\n",
" ax = axes[i, 0]\n",
" ax.hist(data, bins=50, edgecolor='black', alpha=0.7, color=color)\n",
" ax.axvline(np.median(data), color='red', linestyle='--', \n",
" label=f'Median: {np.median(data):.2f} µm')\n",
" ax.axvline(np.mean(data), color='orange', linestyle='--',\n",
" label=f'Mean: {np.mean(data):.2f} µm')\n",
" ax.set_xlabel(f'{label} (µm)', fontsize=11)\n",
" ax.set_ylabel('Count', fontsize=11)\n",
" ax.set_title(f'{chr(65+i*2)}. Distribution of {title}', fontweight='bold')\n",
" ax.legend()\n",
" ax.grid(True, alpha=0.3, axis='y')\n",
" \n",
" # CDF\n",
" ax = axes[i, 1]\n",
" sorted_data = np.sort(data)\n",
" cumulative = np.arange(1, len(sorted_data) + 1) / len(sorted_data)\n",
" ax.plot(sorted_data, cumulative, 'b-', linewidth=2)\n",
" ax.axhline(0.9, color='gray', linestyle=':', alpha=0.7)\n",
" ax.axvline(np.percentile(data, 90), color='red', linestyle='--',\n",
" label=f'90th percentile: {np.percentile(data, 90):.2f} µm')\n",
" ax.set_xlabel(f'{label} (µm)', fontsize=11)\n",
" ax.set_ylabel('Cumulative Proportion', fontsize=11)\n",
" ax.set_title(f'{chr(65+i*2+1)}. Cumulative {title}', fontweight='bold')\n",
" ax.legend()\n",
" ax.grid(True, alpha=0.3)\n",
" \n",
" plt.tight_layout()\n",
" return fig\n",
"\n",
"\n",
"fig = plot_comparison_metrics(original_points, traced_points, None, None)\n",
"plt.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The retraced reconstruction achieves sub-voxel alignment with the original. \n",
"\n",
"**Panel A** shows most point-to-point distances cluster tightly around 0.3–0.5 µm, with a median of 0.45 µm—approximately equal to the isotropic voxel size (0.48 µm). The right-skewed distribution indicates a small fraction of outliers extending to 2–3 µm perhaps at branch points or low-signal regions. \n",
"\n",
"**Panel B** confirms that 90% of all nodes lie within 0.81 µm of their nearest counterpart, demonstrating that A* path tracing successfully recovers the original trajectory at the fundamental imaging resolution.\n",
"\n",
"\n",
"## Refinement: Advanced Adjustments\n",
"\n",
"So far we've only looked at node coordinates. Let's look at their radii:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[main] INFO smile.stat.distribution.GaussianMixture - The BIC of Mixture(12)[0.15 x Gaussian Distribution(0.5389, 0.0664) + 0.19 x Gaussian Distribution(0.5769, 0.0787) + 0.14 x Gaussian Distribution(0.6586, 0.1268) + 0.10 x Gaussian Distribution(0.8182, 0.1457) + 0.09 x Gaussian Distribution(0.9657, 0.1300) + 0.09 x Gaussian Distribution(1.0899, 0.1207) + 0.08 x Gaussian Distribution(1.1988, 0.1180) + 0.06 x Gaussian Distribution(1.3175, 0.1274) + 0.05 x Gaussian Distribution(1.4438, 0.1233) + 0.03 x Gaussian Distribution(1.5529, 0.1128) + 0.02 x Gaussian Distribution(1.6476, 0.1078) + 0.01 x Gaussian Distribution(1.7426, 0.1149)] = -242.9974\n"
]
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def plot_radii_distributions(trees):\n",
" from pysnt.analysis import TreeStatistics\n",
" hists = []\n",
" for tree in trees:\n",
" stats = TreeStatistics(tree)\n",
" hist = stats.getHistogram(\"node radius\")\n",
" hists.append(hist)\n",
" pysnt.display(hists)\n",
"\n",
"plot_radii_distributions([original_tree, fitted_tree])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The retraced tree shows a rightward-shifted distribution with larger radii overall. These outliers typically arise at branch points—where cross-sections capture the junction's wider profile, or in regions where signal from adjacent neurites bleeds into the sampling window. The broader IQR (0.57 vs 0.42 µm) and higher standard deviation (0.35 vs 0.28 µm) reflect this contamination.\n",
"\n",
"A practical correction is to identify outliers and replace them with values interpolated from neighboring nodes (You can read more about this approach [here](https://imagej.net/plugins/snt/manual#refinefit-)). This is exactly what {class}`pysnt.Path``.sanitizeRadii()` does. Two variants are available:\n",
"\n",
"- **Predicate-based**: `sanitizeRadii(lambda r: r < 0.6 or r > 2.6, True)` — accepts a lambda function defining invalid radii\n",
"- **Range-based**: `sanitizeRadii(0.6, 2.6, True)` — accepts explicit min/max bounds\n",
"\n",
"The boolean `apply` argument controls whether corrections are applied in-place (`True`) or only previewed (`False`). Since we know the valid radius range from the original reconstruction, we'll use the range-based variant:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Fixed 69 radii across 16 paths\n"
]
}
],
"source": [
"def sanitize_radii(tree, min_radius, max_radius):\n",
" \"\"\"\n",
" Fix invalid radii across all paths using interpolation.\n",
" \n",
" Parameters\n",
" ----------\n",
" tree : Tree\n",
" The tree to process\n",
" min_radius : float\n",
" minimum valid radius (inclusive)\n",
" max_radius : float\n",
" maximum valid radius (inclusive)\n",
" \n",
" Returns\n",
" -------\n",
" Tree\n",
" The input tree with fixed radii\n",
" \"\"\"\n",
" fixed_count = 0\n",
" skipped_paths = [] # Track skipped paths\n",
" \n",
" for path in tree.list():\n",
" \n",
" # sanitizeRadii returns a dictionary of corrected (node index, radius) pairs\n",
" result = path.sanitizeRadii(min_radius, max_radius, True)\n",
" if result is None or len(result) == 0:\n",
" \n",
" # Path has fewer than 2 nodes (no interpolation possible) or\n",
" # no corrections needed (all radii are already within range)\n",
" skipped_paths.append(path)\n",
" else:\n",
" fixed_count += len(result)\n",
"\n",
" print(f\"Fixed {fixed_count} radii across {len(tree.list())-len(skipped_paths)} paths\")\n",
" return tree\n",
"\n",
"# Fix radii: Eliminate values outside [0.10, 1.55] µm\n",
"fitted_tree = sanitize_radii(fitted_tree, .10, 1.55)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Several radii were adjusted with interpolated values. Let's look at the new distribution:"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[main] INFO smile.stat.distribution.GaussianMixture - The BIC of Mixture(7)[0.19 x Gaussian Distribution(0.5528, 0.0762) + 0.21 x Gaussian Distribution(0.6058, 0.1094) + 0.15 x Gaussian Distribution(0.7336, 0.1650) + 0.12 x Gaussian Distribution(0.9270, 0.1676) + 0.11 x Gaussian Distribution(1.0924, 0.1515) + 0.11 x Gaussian Distribution(1.2369, 0.1451) + 0.10 x Gaussian Distribution(1.3599, 0.1243)] = -89.3491\n",
"[main] INFO smile.stat.distribution.GaussianMixture - The BIC of Mixture(8)[0.16 x Gaussian Distribution(0.5439, 0.0692) + 0.20 x Gaussian Distribution(0.5865, 0.0887) + 0.15 x Gaussian Distribution(0.6835, 0.1397) + 0.11 x Gaussian Distribution(0.8539, 0.1523) + 0.10 x Gaussian Distribution(1.0082, 0.1379) + 0.10 x Gaussian Distribution(1.1412, 0.1315) + 0.10 x Gaussian Distribution(1.2695, 0.1311) + 0.08 x Gaussian Distribution(1.3820, 0.1113)] = -81.5542\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_radii_distributions([original_tree, fitted_tree])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The retraced tree now closely matches the original distribution, without the outliers present in earlier iterations. Core statistics show excellent agreement: Q1 (0.57 vs 0.56 µm) and median (0.79 vs 0.74 µm) differ by less than 7%, confirming that the fitting pipeline captures the true neurite thickness.\n",
"\n",
"The slightly broader IQR (0.55 vs 0.42 µm) and higher mean (0.85 vs 0.79 µm) in the traced tree likely reflect methodological differences: cross-sectional intensity fitting tends to estimate slightly larger radii than manual annotation.\n",
"\n",
"Let's look at direct differences:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Extract radii from both trees\n",
"original_radii = np.array([node.getRadius() for node in original_tree.getNodes() if node.getRadius() > 0])\n",
"fitted_radii = np.array([node.getRadius() for node in fitted_tree.getNodes() if node.getRadius() > 0])\n",
"\n",
"fig = plot_comparison_metrics(None, None, original_radii, fitted_radii)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Once more the fitted radii show strong agreement with the original reconstruction.\n",
"\n",
"**Panel A** Reveals a peak near zero with most differences concentrated below 0.3 µm—approximately 60% of the isotropic voxel size (0.48 µm). The median difference of 0.18 µm indicates that typical radius estimates deviate by less than half a voxel from the ground truth.\n",
"\n",
"**Panel B** The monotonic CDF with a steep initial rise suggests consistent fitting across the reconstruction, without step artifacts that would indicate systematic biases at specific radius values. The right-skewed tail extending to ~1.2 µm reflects residual disagreement at challenging locations—likely branch points or perhaps regions of satured/dim signal."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
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"# Clean up resources\n",
"#pysnt.dispose()"
]
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"## Summary\n",
"\n",
"This tutorial established a programmatic workflow for optimizing neuronal reconstructions by retracing paths through original image data. A strategy complemented by fitting cross-sectional profiles to estimate neurite thickness, and sanitization of outlier radii through interpolation\n",
"\n",
"This workflow is applicable to:\n",
"\n",
"- **Validating** existing reconstructions against image data\n",
"- **Refining** coarse or automated tracings\n",
"- **Enriching** centerline skeletons with thickness information\n",
"- **Generating** high-fidelity ground truth for machine learning pipelines\n",
"\n",
"\n",
"## Follow-up Questions\n",
"\n",
"1. We used default A* settings throughout. How do different cost functions (e.g., reciprocal vs. difference-based) affect path accuracy and computation time?\n",
"\n",
"2. The radius sanitization used fixed bounds derived from the original reconstruction. How would you determine appropriate bounds for a novel dataset without ground truth? (hint: Search [SNT's manual](https://imagej.net/plugins/snt/manual) for local thickness)\n",
"\n",
"3. Reconstruction accuracy may vary across branch orders (e.g., primary dendrites vs. terminal branches). Would adaptive fitting parameters (e.g., varying cross-section radius, or adapting different fallback strategies on a per branch basis) improve results?\n",
"\n",
"\n",
"## Data Sources and References\n",
"\n",
"Data used in this notebook is from the [DIADEM Challenge](https://diadem.janelia.org/) dataset. The relevant publications are:\n",
"\n",
"- Brown KM, Barrionuevo G, Canty AJ, et al. The DIADEM data sets: representative light microscopy images of neuronal morphology to advance automation of digital reconstructions. Neuroinformatics. 2011;9(2-3):143-157. doi:[10.1007/s12021-010-9095-5](https://doi.org/10.1007/s12021-010-9095-5)\n",
"\n",
"- Jefferis GS, Potter CJ, Chan AM, et al. Comprehensive maps of Drosophila higher olfactory centers: spatially segregated fruit and pheromone representation. Cell. 2007;128(6):1187-1203. doi:[10.1016/j.cell.2007.01.040](https://doi.org/10.1016/j.cell.2007.01.040)\n",
"\n",
"See [SNT citation](https://imagej.net/plugins/snt/faq#how-do-i-cite-snt) for details on how to properly cite SNT."
]
}
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