notebooks/7_timelapse_segmentation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8e09a3b8",
   "metadata": {},
   "source": [
    "## Timelapse Segmentation\n",
    "\n",
    "The goal of this notebook is twofold:\n",
    "1. Exemplify how to access SNT without having to specify a local Fiji install\n",
    "2. Exemplify how to analyze a time-lapse image previously skeletonized. For details, see this [forum discussion](https://forum.image.sc/t/filament-analysis-timelapse/59567/6?u=tferr)\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Warning:</b> Until <a href=\"https://github.com/morphonets/SNT/issues/108\">this issue</a> is solved, it won't be possible to initialize the latest version of SNT using the <tt>imagej.init(['sc.fiji:fiji', 'org.morphonets:SNT']</tt> strategy.\n",
    "    In the interim, please use version 4.0.3 (as specified below), or use the ijfinder.py strategy as in previous notebooks.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8c3394cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import imagej\n",
    "from scyjava import jimport\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.pyplot import figure\n",
    "from scipy.spatial.distance import directed_hausdorff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e63de056",
   "metadata": {},
   "outputs": [],
   "source": [
    "ij = imagej.init(['sc.fiji:fiji', 'org.morphonets:SNT:4.0.3'], mode='interactive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a3e8d091",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Replace with your skeleton image\n",
    "impath = \"../images/skeleton_timeseries.tif\" # relative path to demo image\n",
    "dataset = ij.io().open(impath)\n",
    "\n",
    "# Let's find out the time dimension index and the total number of frames\n",
    "Axes = jimport(\"net.imagej.axis.Axes\")\n",
    "frame_dim_idx = dataset.dimensionIndex(Axes.TIME)\n",
    "n_frames = dataset.dimension(frame_dim_idx)\n",
    "\n",
    "# Plot the last frame since it contains the fully developed structures.\n",
    "# From this, we gather that we should be able to segment the developmental stages\n",
    "# of three distinct objects.\n",
    "last_frame = ij.op().transform().hyperSliceView(dataset, frame_dim_idx, n_frames-1)\n",
    "\n",
    "figure(figsize=(10,10))\n",
    "ij.py.show(last_frame, cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74531cf1",
   "metadata": {},
   "source": [
    "The general approach is to obtain reconstructions of the connected components in the skeleton image at each frame, and to associate each reconstruction with it's closest matching \"child\" in the next frame, if one exists. \n",
    "\n",
    "In this instance, it is natural to represent the reconstructions as graph-theory objects, namely [trees](https://en.wikipedia.org/wiki/Tree_(graph_theory). We can use the [SkeletonConverter](https://javadoc.scijava.org/SNT/sc/fiji/snt/analysis/SkeletonConverter.html) class to generate these kinds of graph objects from a pre-skeletonized (or otherwise binary) image. Each graph will represent a single connected component in the skeleton image at frame t, with the vertex set given by the connected voxels defining the component and edges linking adjacent voxels. The concrete graph data type is [DirectedWeightedGraph](https://javadoc.scijava.org/SNT/sc/fiji/snt/analysis/graph/DirectedWeightedGraph.html), which encapsulates various methods for manipulation and analysis of the resulting tree structure.\n",
    "\n",
    "To construct a \"lineage\" of graph objects, we can store two pointers along with a graph. One for the parent object in the previous frame, and one for the child object in the next frame. The term \"lineage\" is used rather loosely here, as we assume an object may have at most one child in the next frame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a1cb610d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import a couple helpful Java classes\n",
    "ImageJFunctions = jimport(\"net.imglib2.img.display.imagej.ImageJFunctions\")\n",
    "SkeletonConverter = jimport(\"sc.fiji.snt.analysis.SkeletonConverter\")\n",
    "\n",
    "class LineageNode:\n",
    "    \"\"\"Minimal class representing a node in a doubly linked list. We can use this to wrap \n",
    "    a graph object with its matched \"child\" in the next frame and the matched \"parent\" \n",
    "    in the previous frame, along with the index of the frame the graph exists in.\"\"\"\n",
    "    \n",
    "    def __init__(self, graph, parent, child, frame):\n",
    "        self.graph = graph\n",
    "        self.parent = parent\n",
    "        self.child = child\n",
    "        self.frame = frame\n",
    "        \n",
    "\n",
    "# Extract graph objects from the skeletonized image at each frame\n",
    "lineage_nodes_by_frame = {}\n",
    "for frame_idx in range(n_frames):\n",
    "    # Extract the image slice at the current frame\n",
    "    frame_img = ij.op().transform().hyperSliceView(dataset, frame_dim_idx, frame_idx)\n",
    "    # Convert to ImagePlus since that is the data type expected by\n",
    "    # AnalyzeSkeleton_ (and thus SkeletonConverter).\n",
    "    frame_imp = ImageJFunctions.wrap(frame_img, \"\")\n",
    "    # Since the wrapped ImagePlus is a virtual stack, it must be duplicated\n",
    "    # if we want to write to the pixel data. \n",
    "    # Otherwise,the routine will hang forever...\n",
    "    skeletonize = False  # The input is already a skeleton.\n",
    "    converter = SkeletonConverter(frame_imp.duplicate(), skeletonize)\n",
    "    # Obtain the reconstructions at the current frame.\n",
    "    # These structures are represented as directed graphs -- \n",
    "    # specifically, rooted trees. There will be one graph\n",
    "    # for each connected component in the skeleton image at \n",
    "    # the current frame.\n",
    "    graphs = converter.getGraphs()\n",
    "    # Prune components with fewer than 5 connected voxels\n",
    "    graphs = filter(lambda x: x.vertexSet().size() >= 5, graphs)\n",
    "    # Construct a LineageNode instance from each graph object, leaving\n",
    "    # the parent and child fields empty for now. We will fill those\n",
    "    # later when matching objects across frames.\n",
    "    lineage_nodes = []\n",
    "    for g in graphs:\n",
    "        lineage_nodes.append(LineageNode(g, None, None, frame_idx))\n",
    "    # Store all the nodes at the current frame in a dictionary.\n",
    "    # We'll use this when matching graphs between frames\n",
    "    lineage_nodes_by_frame[frame_idx] = lineage_nodes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19804fe6",
   "metadata": {},
   "source": [
    "We will naively match trees between frames brute-force by computing the [Hausdorff distance](https://en.wikipedia.org/wiki/Hausdorff_distance) between the point sets of a query graph and all the graphs in the next frame. If the amount of growth between frames is small enough and a single object does not split into two or merge with another, this should work reasonably well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4b1e1ad6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def graph_to_points(graph):\n",
    "    \"\"\"Decompose a graph into an m x 3 array of x,y,z coordinates.\n",
    "    If the graph originates from a 2D image, all z coordinates are 0\"\"\"\n",
    "    points = []\n",
    "    for v in graph.vertexSet():\n",
    "        points.append([v.getX(), v.getY(), v.getZ()])\n",
    "    return np.array(points)\n",
    "\n",
    "\n",
    "def find_match(query_node, target_nodes, max_distance):\n",
    "    \"\"\"Match a query LineageNode against a set of target LineageNodes by finding\n",
    "    the target with minimum hausdorff distance to the query.\n",
    "    If the best matching target is beyond the maximum distance cutoff,\n",
    "    return no match.\"\"\"\n",
    "    query_points = graph_to_points(query_node.graph)\n",
    "    min_dx = float(\"inf\")\n",
    "    best_match = None\n",
    "    for target in target_nodes:\n",
    "        target_points = graph_to_points(target.graph)\n",
    "        dx = max(\n",
    "            directed_hausdorff(query_points, target_points)[0], \n",
    "            directed_hausdorff(target_points, query_points)[0]\n",
    "        )\n",
    "        if dx < min_dx:\n",
    "            min_dx = dx\n",
    "            best_match = target\n",
    "    if min_dx > max_distance:\n",
    "        return None\n",
    "    return best_match\n",
    "\n",
    "\n",
    "# Brute-force matching of connected components across frames.\n",
    "# If the best candidate is more than max_distance\n",
    "# away from the query, it is rejected.\n",
    "max_distance = 50\n",
    "for frame, nodes in sorted(lineage_nodes_by_frame.items()):\n",
    "    if frame + 1 >= n_frames:\n",
    "        # components in the last frame will have no children\n",
    "        continue\n",
    "    lineage_nodes_at_next_frame = lineage_nodes_by_frame[frame + 1]\n",
    "    # For each node in the current frame,\n",
    "    # find the best match (if one exists) in the next frame.\n",
    "    for n in nodes:\n",
    "        match = find_match(n, lineage_nodes_at_next_frame, max_distance)\n",
    "        if match is not None:\n",
    "            # Assign relationships in both directions\n",
    "            n.child = match\n",
    "            match.parent = n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa34d381",
   "metadata": {},
   "source": [
    "Now we'll define some helper functions to interact with our lineages. We'll have one function that obtains the root nodes (i.e., the set of nodes with no parent) from the set of all nodes, and another that gets all the descendants of a given node. Note that the descendent list is always flat, since each node can have only one child. Finally, we'll have one method that converts a list of our custom LineageNode objects to a list of standard SNT [Tree](https://javadoc.scijava.org/SNT/sc/fiji/snt/Tree.html) objects, as the latter can be passed to SNT's various visualization and analysis routines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6da98cc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_roots(lineage_nodes_by_frame):\n",
    "    \"\"\"Get the list of root nodes (i.e., the set of \n",
    "    nodes with no parent) from the dictionary of LineageNode objects\"\"\"\n",
    "    roots = []\n",
    "    for nodes in lineage_nodes_by_frame.values():\n",
    "        roots.extend(filter(lambda n: n.parent is None, nodes))\n",
    "    return roots\n",
    "\n",
    "\n",
    "def get_descendants(lineage_node):\n",
    "    \"\"\"Get a list of descendants given a LineageNode.\n",
    "    The descendant list includes the given node too.\"\"\"\n",
    "    lineage = []\n",
    "    while lineage_node is not None:\n",
    "        lineage.append(lineage_node)\n",
    "        lineage_node = lineage_node.child\n",
    "    return lineage\n",
    "\n",
    "\n",
    "def lineage_to_trees(lineage_nodes):\n",
    "    \"\"\"Convert a list of LineageNode objects\n",
    "    to a list of Tree objects\"\"\"\n",
    "    lineage_trees = []\n",
    "    for node in lineage_nodes:\n",
    "        # Convert the low-level graph to a high-level\n",
    "        # Tree object, which we can pass to\n",
    "        # various analysis and visualization\n",
    "        # routines.\n",
    "        # See DirectedWeightedGraph#getTree()\n",
    "        tree = node.graph.getTree()\n",
    "        lineage_trees.append(tree)\n",
    "    return lineage_trees"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "253e9f47",
   "metadata": {},
   "source": [
    "The number of roots will give the number of lineages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3c03bec0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 objects detected\n"
     ]
    }
   ],
   "source": [
    "roots = get_roots(lineage_nodes_by_frame)\n",
    "print(len(roots), \"objects detected\")\n",
    "\n",
    "lineages = [lineage_to_trees(get_descendants(r)) for r in roots]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac42d93b",
   "metadata": {},
   "source": [
    "Let's plot the evolution of the largest component and color code by total length at each frame. Since the input image is uncalibrated, length is measured in pixels. For this, we can use the [MultiTreeColorMapper](https://javadoc.scijava.org/SNT/sc/fiji/snt/analysis/MultiTreeColorMapper.html) and [ColorTables](https://javadoc.scijava.org/ImageJ/net/imagej/display/ColorTables.html) classes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6320a54a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 750
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ColorTables = jimport(\"net.imagej.display.ColorTables\")\n",
    "MultiTreeColorMapper = jimport(\"sc.fiji.snt.analysis.MultiTreeColorMapper\")\n",
    "\n",
    "def get_multiviewer(lineage_trees, metric):\n",
    "    mapper = MultiTreeColorMapper(lineage_trees)\n",
    "    mapper.map(metric, ColorTables.ICE)\n",
    "    minmax = mapper.getMinMax()\n",
    "    v = mapper.getMultiViewer()\n",
    "    v.setColorBarLegend(ColorTables.ICE, minmax[0], minmax[1])\n",
    "    return v\n",
    "\n",
    "# The first lineage also happens to be the most interesting in this case\n",
    "viewer = get_multiviewer(lineages[0], MultiTreeColorMapper.LENGTH)\n",
    "viewer.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52cc4ec2",
   "metadata": {},
   "source": [
    "We can also measure [Trees](https://javadoc.scijava.org/SNT/sc/fiji/snt/Tree.html) with [TreeStatistics](https://javadoc.scijava.org/SNT/sc/fiji/snt/analysis/TreeStatistics.html) and [MultiTreeStatistics](https://javadoc.scijava.org/SNT/sc/fiji/snt/analysis/MultiTreeStatistics.html) classes, and plot measurements as a function of time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "67aa77a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x648 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "TreeStatistics = jimport(\"sc.fiji.snt.analysis.TreeStatistics\")\n",
    "MultiTreeStatistics = jimport(\"sc.fiji.snt.analysis.MultiTreeStatistics\")\n",
    "\n",
    "def plot_metric(root_nodes, metric, ax):\n",
    "    # Plot the measurements for each lineage\n",
    "    for i, r in enumerate(roots):\n",
    "        lineage_trees = lineage_to_trees(get_descendants(r))\n",
    "        xs = np.arange(r.frame, r.frame + len(lineage_trees))\n",
    "        ys = [TreeStatistics(tree).getMetric(metric) for tree in lineage_trees]\n",
    "        ax.set_title(f\"{metric} vs Time\")\n",
    "        ax.set_ylabel(f\"{metric}\")\n",
    "        ax.set_xlabel(\"Frame\")\n",
    "        ax.plot(xs, ys, label=f\"object {i}\")\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots(2, 2, figsize=(13,9))\n",
    "plot_metric(roots, MultiTreeStatistics.LENGTH, ax[0][0])\n",
    "plot_metric(roots, MultiTreeStatistics.N_BRANCHES, ax[0][1])    \n",
    "plot_metric(roots, MultiTreeStatistics.WIDTH, ax[1][0])\n",
    "plot_metric(roots, MultiTreeStatistics.HEIGHT, ax[1][1])\n",
    "fig.tight_layout()\n",
    "plt.legend(loc=\"upper left\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c04c280",
   "metadata": {},
   "source": [
    "Exercise for the reader: how might one prune the graphs of spurious micro-branches that interfere with analysis? \n",
    "See [here](https://jgrapht.org/javadoc/org.jgrapht.core/org/jgrapht/Graph.html) for hints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d9747e96",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}