OSCR

Spatio-Temporal Dynamics of Macroglial Cell Organization and Proximity to Blood Vessels During Postnatal Development.

Code ↔ Paper

4 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 4 matches · 1 of them tie a paragraph to a whole file, not to given lines: a weak match, whose lines are not tinted
  1. [1] § Materials and Methods › Image Analysis ↔ src/main/java/VeCell_Tools/Tools.java, lines 1002–1064 · score 0.76 · standard deviation, Analyze Skeleton, branch length, junctions, neighbour, SDI
  2. [2] § Materials and Methods › Image Analysis ↔ src/main/java/VeCell_Tools/Cellpose/CellposeTask.java, the whole file · a weak match · score 0.73 · flow threshold, stitching threshold, pretrained model, Cellpose, diameter
  3. [3] § Materials and Methods › Image Analysis ↔ src/main/java/VeCell_Tools/Cellpose/CellposeTaskSettings.java, lines 61–126 · score 0.69 · cell probability, flow threshold, stitching threshold, Cellpose
  4. [4] § Materials and Methods › Image Analysis ↔ src/main/java/VeCell_Tools/Tools.java, lines 586–642 · score 0.51 · automated thresholding, Gaussian, median, CLIJ, filter

Paper

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The authors' code

Java · 1,151 lines · 46 KB · no license · 2 matches

  1. package VeCell_Tools;
  3. import VeCell_Tools.Cellpose.CellposeTaskSettings;
  4. import VeCell_Tools.Cellpose.CellposeSegmentImgPlusAdvanced;
  5. import fiji.util.gui.GenericDialogPlus;
  6. import ij.IJ;
  7. import ij.ImagePlus;
  8. import ij.ImageStack;
  9. import ij.gui.Plot;
  10. import ij.gui.PolygonRoi;
  11. import ij.gui.Roi;
  12. import ij.io.FileSaver;
  13. import ij.measure.Calibration;
  14. import ij.measure.ResultsTable;
  15. import ij.plugin.ImageCalculator;
  16. import ij.plugin.RGBStackMerge;
  17. import ij.plugin.RoiEnlarger;
  18. import ij.plugin.RoiScaler;
  19. import ij.plugin.filter.Analyzer;
  20. import ij.plugin.filter.ParticleAnalyzer;
  21. import ij.plugin.frame.RoiManager;
  22. import ij.process.AutoThresholder;
  23. import java.awt.Color;
  24. import java.awt.Font;
  25. import java.io.BufferedWriter;
  26. import java.io.File;
  27. import java.io.FileWriter;
  28. import java.io.IOException;
  29. import java.util.ArrayList;
  30. import java.util.Collections;
  31. import java.awt.Rectangle;
  32. import java.util.Arrays;
  33. import java.util.List;
  34. import java.util.stream.IntStream;
  35. import javax.swing.ImageIcon;
  36. import loci.common.services.DependencyException;
  37. import loci.common.services.ServiceException;
  38. import loci.formats.FormatException;
  39. import loci.formats.meta.IMetadata;
  40. import loci.plugins.BF;
  41. import loci.plugins.in.ImporterOptions;
  42. import loci.plugins.util.ImageProcessorReader;
  43. import mcib3d.geom.Object3D;
  44. import mcib3d.geom.Objects3DPopulation;
  45. import mcib3d.image3d.ImageHandler;
  46. import mcib3d.geom2.Object3DInt;
  47. import mcib3d.geom2.Objects3DIntPopulation;
  48. import mcib3d.geom2.measurements.Measure2Distance;
  49. import mcib3d.geom2.measurements.MeasureCentroid;
  50. import mcib3d.geom2.measurements.MeasureIntensity;
  51. import mcib3d.geom2.measurements.MeasureVolume;
  52. import mcib3d.geom2.measurementsPopulation.MeasurePopulationDistance;
  53. import mcib3d.geom2.measurementsPopulation.PairObjects3DInt;
  54. import mcib3d.image3d.ImageFloat;
  55. import mcib3d.image3d.ImageInt;
  56. import mcib3d.image3d.ImageLabeller;
  57. import mcib3d.image3d.distanceMap3d.EDT;
  58. import mcib3d.spatial.descriptors.G_Function;
  59. import mcib3d.spatial.descriptors.SpatialDescriptor;
  60. import mcib3d.spatial.sampler.SpatialModel;
  61. import mcib3d.spatial.sampler.SpatialRandomHardCore;
  62. import mcib3d.utils.ThreadUtil;
  63. import net.haesleinhuepf.clij.clearcl.ClearCLBuffer;
  64. import net.haesleinhuepf.clij2.CLIJ2;
  65. import net.haesleinhuepf.clijx.bonej.BoneJSkeletonize3D;
  66. import org.apache.commons.io.FilenameUtils;
  67. import org.apache.commons.math3.stat.StatUtils;
  68. import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics;
  69. import sc.fiji.analyzeSkeleton.AnalyzeSkeleton_;
  70. import sc.fiji.analyzeSkeleton.Edge;
  71. import sc.fiji.analyzeSkeleton.Graph;
  72. import sc.fiji.analyzeSkeleton.Point;
  73. import sc.fiji.analyzeSkeleton.SkeletonResult;
  76. /**
  77. * @author ORION-CIRB
  78. */
  79. public class Tools {
  81. public final ImageIcon icon = new ImageIcon(this.getClass().getResource("/Orion_icon.png"));
  82. private final String helpUrl = "https://github.com/orion-cirb/VeCell/tree/version5";
  83. public CLIJ2 clij2 = CLIJ2.getInstance();
  85. private BufferedWriter resultsGlobal;
  86. private BufferedWriter resultsDetail;
  88. private Calibration cal;
  89. private double pixelVol;
  91. String[] chDialog = new String[]{"Astrocytes", "Vessels (optional)"};
  92. public int imgSeries = 0;
  93. public int roiScaling = 9;
  94. public double roiDilation = 50; // um
  96. public String cellposeEnvDir = IJ.isWindows()? System.getProperty("user.home")+File.separator+"miniconda3"+File.separator+"envs"+File.separator+"CellPose" : "/opt/miniconda3/envs/cellpose";
  97. public final String cellposeModelDir = IJ.isWindows()? System.getProperty("user.home")+File.separator+".cellpose"+File.separator+"models"+File.separator : "";
  98. public String cellposeModel = "cyto2_sox9_p5-15-60_27-11-24";
  99. public int cellposeDiam = 20;
  100. public double cellposeStitchTh = 0.5;
  101. public boolean filterOneZ = true;
  102. public double minCellVol = 300; // um3
  103. public double maxCellVol = 3000; // um3
  105. private int nbNei = 10; // K-nearest neighbors
  106. private boolean computeGFunction = false;
  107. private int nbRandomSamples = 50;
  109. private double dog1Sigma1 = 4;
  110. private double dog1Sigma2 = 8;
  111. private String vesselThMet1 = "Triangle";
  112. private boolean dog2 = true;
  113. private double dog2Sigma1 = 7;
  114. private double dog2Sigma2 = 14;
  115. private String vesselThMet2 = "Triangle";
  116. private double maxHoleArea = 100; // µm2
  117. public double minVesselVol = 600; // um3
  118. private double minVesselLength = 10; // um
  121. /**
  122. * Display a message in the ImageJ console and status bar
  123. */
  124. public void print(String log) {
  125. System.out.println(log);
  126. IJ.showStatus(log);
  127. }
  130. /**
  131. * Flush and close an image
  132. */
  133. public void closeImage(ImagePlus img) {
  134. img.flush();
  135. img.close();
  136. }
  139. /**
  140. * Check that needed modules are installed
  141. */
  142. public boolean checkInstalledModules() {
  143. ClassLoader loader = IJ.getClassLoader();
  144. try {
  145. loader.loadClass("net.haesleinhuepf.clij2.CLIJ2");
  146. } catch (ClassNotFoundException e) {
  147. IJ.log("CLIJ not installed, please install from update site");
  148. return false;
  149. }
  150. try {
  151. loader.loadClass("mcib3d.geom2.Object3DInt");
  152. } catch (ClassNotFoundException e) {
  153. IJ.log("3D ImageJ Suite not installed, please install from update site");
  154. return false;
  155. }
  156. return true;
  157. }
  160. /**
  161. * Get extension of the first image found in the folder
  162. */
  163. public String findImageType(File imagesFolder) {
  164. String ext = "";
  165. String[] files = imagesFolder.list();
  166. for (String name : files) {
  167. String fileExt = FilenameUtils.getExtension(name);
  168. switch (fileExt) {
  169. case "nd" :
  170. ext = fileExt;
  171. break;
  172. case "nd2" :
  173. ext = fileExt;
  174. break;
  175. case "lif" :
  176. ext = fileExt;
  177. break;
  178. case "czi" :
  179. ext = fileExt;
  180. break;
  181. case "ics" :
  182. ext = fileExt;
  183. break;
  184. case "ics2" :
  185. ext = fileExt;
  186. break;
  187. case "lsm" :
  188. ext = fileExt;
  189. break;
  190. case "tif" :
  191. ext = fileExt;
  192. break;
  193. case "tiff" :
  194. ext = fileExt;
  195. break;
  196. }
  197. }
  198. return(ext);
  199. }
  202. /**
  203. * Get images with given extension in folder
  204. */
  205. public ArrayList<String> findImages(String imagesFolder, String imageExt) {
  206. File inDir = new File(imagesFolder);
  207. String[] files = inDir.list();
  208. ArrayList<String> images = new ArrayList();
  209. for (String f : files) {
  210. String fileExt = FilenameUtils.getExtension(f);
  211. if (fileExt.equals(imageExt) && !f.startsWith("."))
  212. images.add(imagesFolder + f);
  213. }
  214. Collections.sort(images);
  215. return(images);
  216. }
  219. /**
  220. * Get image calibration
  221. */
  222. public void findImageCalib(IMetadata meta) {
  223. cal = new Calibration();
  224. cal.pixelWidth = meta.getPixelsPhysicalSizeX(0).value().doubleValue();
  225. cal.pixelHeight = cal.pixelWidth;
  226. if (meta.getPixelsPhysicalSizeZ(0) != null)
  227. cal.pixelDepth = meta.getPixelsPhysicalSizeZ(0).value().doubleValue();
  228. else
  229. cal.pixelDepth = 1;
  230. cal.setUnit("microns");
  231. System.out.println("XY calibration = " + cal.pixelWidth + ", Z calibration = " + cal.pixelDepth);
  232. }
  235. /**
  236. * Get channels name and add None at the end of channels list
  237. * @throws loci.common.services.DependencyException
  238. * @throws loci.common.services.ServiceException
  239. * @throws loci.formats.FormatException
  240. * @throws java.io.IOException
  241. */
  242. public String[] findChannels(String imageName, IMetadata meta, ImageProcessorReader reader) throws DependencyException, ServiceException, FormatException, IOException {
  243. int chs = reader.getSizeC();
  244. String[] channels = new String[chs+1];
  245. String imageExt = FilenameUtils.getExtension(imageName);
  246. switch (imageExt) {
  247. case "nd" :
  248. for (int n = 0; n < chs; n++)
  249. channels[n] = (meta.getChannelName(0, n).toString().equals("")) ? Integer.toString(n) : meta.getChannelName(0, n).toString();
  250. break;
  251. case "nd2" :
  252. for (int n = 0; n < chs; n++)
  253. channels[n] = (meta.getChannelName(0, n).toString().equals("")) ? Integer.toString(n) : meta.getChannelName(0, n).toString();
  254. break;
  255. case "lif" :
  256. for (int n = 0; n < chs; n++)
  257. if (meta.getChannelID(0, n) == null || meta.getChannelName(0, n) == null)
  258. channels[n] = Integer.toString(n);
  259. else
  260. channels[n] = meta.getChannelName(0, n).toString();
  261. break;
  262. case "czi" :
  263. for (int n = 0; n < chs; n++)
  264. channels[n] = (meta.getChannelFluor(0, n).toString().equals("")) ? Integer.toString(n) : meta.getChannelFluor(0, n).toString();
  265. break;
  266. case "ics" :
  267. for (int n = 0; n < chs; n++)
  268. channels[n] = meta.getChannelEmissionWavelength(0, n).value().toString();
  269. break;
  270. case "ics2" :
  271. for (int n = 0; n < chs; n++)
  272. channels[n] = meta.getChannelEmissionWavelength(0, n).value().toString();
  273. break;
  274. default :
  275. for (int n = 0; n < chs; n++)
  276. channels[n] = Integer.toString(n);
  277. }
  278. channels[chs] = "None";
  279. return(channels);
  280. }
  283. /**
  284. * Generate dialog box
  285. */
  286. public String[] dialog(String[] chMeta) {
  287. GenericDialogPlus gd = new GenericDialogPlus("Parameters");
  288. gd.setInsets​(0, 180, 0);
  289. gd.addImage(icon);
  291. gd.addMessage("Channels", new Font("Monospace", Font.BOLD, 12), Color.blue);
  292. for (int n = 0; n < chDialog.length; n++)
  293. gd.addChoice(chDialog[n]+": ", chMeta, chMeta[n]);
  295. gd.addMessage("ROIs", new Font("Monospace", Font.BOLD, 12), Color.blue);
  296. gd.addNumericField("Scaling factor: ", roiScaling, 0);
  298. gd.addMessage("Astrocytes detection", new Font("Monospace", Font.BOLD, 12), Color.blue);
  299. gd.addStringField("Cellpose model: ", cellposeModel);
  300. gd.addToSameRow();
  301. gd.addNumericField("Cellpose diameter: ", cellposeDiam, 0);
  302. gd.addCheckbox("Delete single-slice cells", filterOneZ);
  303. gd.addNumericField("Min volume (µm3): ", minCellVol, 2);
  304. gd.addToSameRow();
  305. gd.addNumericField("Max volume (µm3): ", maxCellVol, 2);
  307. gd.addMessage("Astrocytes spatial distribution", new Font("Monospace", Font.BOLD, 12), Color.blue);
  308. gd.addNumericField("Neighbors nb: ", nbNei, 0);
  309. gd.addCheckbox("Compute G-function", computeGFunction);
  310. gd.addToSameRow();
  311. gd.addNumericField("Random samples nb: ", nbRandomSamples, 0);
  313. String[] methods = AutoThresholder.getMethods();
  314. gd.addMessage("Vessels segmentation", new Font("Monospace", Font.BOLD, 12), Color.blue);
  315. gd.addMessage("DoG filter 1", new Font("Monospace", Font.PLAIN, 12), Color.blue);
  316. gd.addNumericField("Sigma 1: ", dog1Sigma1, 2);
  317. gd.addToSameRow();
  318. gd.addNumericField("Sigma 2: ", dog1Sigma2, 2);
  319. gd.addChoice("Threshold: ", methods, vesselThMet1);
  320. gd.addMessage("DoG filter 2", new Font("Monospace", Font.PLAIN, 12), Color.blue);
  321. gd.addCheckbox("Apply filter", dog2);
  322. gd.addNumericField("Sigma 1: ", dog2Sigma1, 2);
  323. gd.addToSameRow();
  324. gd.addNumericField("Sigma 2: ", dog2Sigma2, 2);
  325. gd.addChoice("Threshold: ", methods, vesselThMet2);
  326. gd.addNumericField("Max hole area (µm2): ", maxHoleArea, 2);
  327. gd.addNumericField("Min volume (µm3): ", minVesselVol, 2);
  328. gd.addToSameRow();
  329. gd.addNumericField("Min length (µm): ", minVesselLength, 2);
  331. gd.addMessage("Image calibration", new Font("Monospace", Font.BOLD, 12), Color.blue);
  332. gd.addNumericField("XY pixel size (µm): ", cal.pixelWidth, 4);
  333. gd.addToSameRow();
  334. gd.addNumericField("Z pixel size (µm): ", cal.pixelDepth, 4);
  336. gd.addHelp(helpUrl);
  337. gd.showDialog();
  339. String[] chOrder = new String[chDialog.length];
  340. for (int n = 0; n < chOrder.length; n++)
  341. chOrder[n] = gd.getNextChoice();
  343. roiScaling = (int) gd.getNextNumber();
  344. if (roiScaling <= 0) {
  345. roiScaling = 1;
  346. print("ERROR: ROIs cannot be scaled by zero or negative values. ROI scaling factor set to 1.");
  347. }
  349. cellposeModel = gd.getNextString();
  350. cellposeDiam = (int) gd.getNextNumber();
  351. filterOneZ = gd.getNextBoolean();
  352. minCellVol = gd.getNextNumber();
  353. maxCellVol = gd.getNextNumber();
  355. nbNei = (int)gd.getNextNumber();
  356. computeGFunction = gd.getNextBoolean();
  357. nbRandomSamples = (int)gd.getNextNumber();
  359. dog1Sigma1 = (int) gd.getNextNumber();
  360. dog1Sigma2 = (int) gd.getNextNumber();
  361. vesselThMet1 = gd.getNextChoice();
  362. dog2 = gd.getNextBoolean();
  363. dog2Sigma1 = (int) gd.getNextNumber();
  364. dog2Sigma2 = (int) gd.getNextNumber();
  365. vesselThMet2 = gd.getNextChoice();
  366. maxHoleArea = gd.getNextNumber();
  367. minVesselVol = gd.getNextNumber();
  368. minVesselLength = gd.getNextNumber();
  370. cal.pixelWidth = cal.pixelHeight = gd.getNextNumber();
  371. cal.pixelDepth = gd.getNextNumber();
  372. pixelVol = cal.pixelWidth * cal.pixelHeight * cal.pixelDepth;
  374. if (gd.wasCanceled())
  375. chOrder = null;
  376. return(chOrder);
  377. }
  380. /**
  381. * Save images specific channel before sending it to QuantileBasedNormalization plugin
  382. * @throws Exception
  383. */
  384. public void saveChannel(ArrayList<String> imgFiles, int series, int channel, String normDir, String extension) throws Exception {
  385. try {
  386. for (String f : imgFiles) {
  387. String imgName = FilenameUtils.getBaseName(f);
  389. ImporterOptions options = new ImporterOptions();
  390. options.setId(f);
  391. options.setSplitChannels(true);
  392. options.setColorMode(ImporterOptions.COLOR_MODE_GRAYSCALE);
  393. options.setQuiet(true);
  395. // Open and save vessels channel
  396. ImagePlus imgVessels = openChannel(options, series, channel);
  397. IJ.saveAs(imgVessels, "Tiff", normDir+imgName+extension);
  398. closeImage(imgVessels);
  399. }
  400. } catch (Exception e) {
  401. throw e;
  402. }
  403. }
  406. public ImagePlus openChannel(ImporterOptions options, int series, int channel) throws FormatException, IOException {
  407. options.setCBegin(series, channel);
  408. options.setCEnd(series, channel);
  409. ImagePlus img = BF.openImagePlus(options)[0];
  410. return(img);
  411. }
  414. /**
  415. * Delete images specific channel after it was sent to QuantileBasedNormalization plugin
  416. * @throws Exception
  417. */
  418. public void deleteChannel(String dir, ArrayList<String> imageFiles, String extension) throws Exception {
  419. try {
  420. for (String f : imageFiles) {
  421. String rootName = FilenameUtils.getBaseName(f);
  422. new File(dir+rootName+extension).delete();
  423. }
  424. } catch (Exception e) {
  425. throw e;
  426. }
  427. }
  430. public List<Roi> loadRois(String imageDir, String imgName) {
  431. String roiName = imageDir+imgName+".zip";
  432. if (! new File(roiName).exists()) {
  433. print("ERROR: No ROI file found for image "+imgName+". Image not analyzed.");
  434. return(null);
  435. } else {
  436. RoiManager rm = new RoiManager(false);
  437. rm.runCommand("Open", roiName);
  438. List<Roi> rois = Arrays.asList(rm.getRoisAsArray());
  440. for (Roi roi : rois) {
  441. if(roi.getName().split(" ").length != 2) {
  442. print("ERROR: ROIs not correctly named in "+imgName +". Image not analyzed. Expected format: \"position layerName\" (e.g. \"0095-0429 l2\").");
  443. return(null);
  444. }
  445. }
  446. return(rois);
  447. }
  448. }
  451. /**
  452. * Scale ROIs
  453. */
  454. public List<Roi> scaleRois(List<Roi> rois, int scale, IMetadata meta, String imgName) {
  455. List<Roi> scaledRois = new ArrayList<Roi>();
  456. for (Roi roi : rois) {
  457. Roi scaledRoi = new RoiScaler().scale(roi, scale, scale, false);
  458. Rectangle rect = roi.getBounds();
  459. scaledRoi.setLocation(rect.x*scale, rect.y*scale);
  460. scaledRoi.setName(roi.getName());
  461. scaledRois.add(scaledRoi);
  462. }
  464. for (Roi roi : scaledRois) {
  465. Rectangle rect = roi.getBounds();
  466. if(rect.x < 0 || rect.x < 0 || rect.x+rect.width > meta.getPixelsSizeX(0).getValue() || rect.y+rect.height > meta.getPixelsSizeY(0).getValue()) {
  467. print("ERROR: ROIs exceed image size in "+imgName +". Image not analyzed. Check scaling factor.");
  468. return(null);
  469. }
  470. }
  471. return scaledRois;
  472. }
  475. /**
  476. * Get bounding box of multiple dilated ROIs combined together
  477. */
  478. public Roi getBoundingBox(List<Roi> rois) {
  479. Rectangle rect0 = RoiEnlarger.enlarge(rois.get(0), roiDilation/cal.pixelWidth).getBounds();
  480. int minX = rect0.x, minY = rect0.y, maxX = rect0.x+rect0.width, maxY = rect0.y+rect0.height;
  481. for (Roi roi : rois) {
  482. Rectangle rect = RoiEnlarger.enlarge(roi, roiDilation/cal.pixelWidth).getBounds();
  483. if(rect.x < minX) minX = rect.x;
  484. if(rect.y < minY) minY = rect.y;
  485. if(rect.x+rect.width > maxX) maxX = rect.x+rect.width;
  486. if(rect.y+rect.height > maxY) maxY = rect.y+rect.height;
  487. }
  488. minX = Math.max(minX, 0);
  489. minY = Math.max(minY, 0);
  490. return new Roi(minX, minY, maxX-minX, maxY-minY);
  491. }
  494. /**
  495. * Translate ROIs
  496. */
  497. public void translateRois(List<Roi> rois, Roi bBox) {
  498. Rectangle rectBBox = bBox.getBounds();
  499. for (Roi roi: rois) {
  500. Rectangle rectRoi = roi.getBounds();
  501. roi.setLocation(rectRoi.x-rectBBox.x, rectRoi.y-rectBBox.y);
  502. }
  503. }
  506. /**
  507. * Save ROIs in a zip file
  508. */
  509. public void saveRois(List<Roi> rois, String outDir, String imgName) {
  510. RoiManager rm = new RoiManager(false);
  511. for(Roi roi: rois) {
  512. String layerName = roi.getName().split(" ")[1];
  513. rm.addRoi(roi);
  514. String roiName = rm.getName(rm.getCount()-1) + " " + layerName;
  515. rm.rename(rm.getCount()-1, roiName);
  516. }
  517. rm.deselect();
  518. rm.save(outDir+imgName+"_rois.zip");
  519. rm.close();
  520. }
  523. /**
  524. * Crop stack around ROI
  525. */
  526. public ImagePlus cropImage(ImagePlus img, Roi roi) {
  527. img.setRoi(roi);
  528. ImagePlus imgCrop = img.crop("stack");
  529. img.deleteRoi();
  530. return(imgCrop);
  531. }
  534. /*
  535. * Look for all 3D cells in a Z-stack:
  536. * - apply Cellpose 2D slice by slice
  537. * - let CellPose reconstruct cells in 3D using the stitch_threshold parameter
  538. */
  539. public ImagePlus cellposeDetection(ImagePlus imgIn) throws IOException{
  540. ImagePlus img = imgIn.duplicate();
  542. // Define Cellpose settings
  543. CellposeTaskSettings settings = new CellposeTaskSettings(cellposeModel.equals("cyto")? cellposeModel : cellposeModelDir+cellposeModel, 1, cellposeDiam, cellposeEnvDir); // need to add Cellpose models folder path if own model (for Windows only, not Linux)
  544. settings.setStitchThreshold(cellposeStitchTh);
  545. settings.useGpu(true);
  547. // Run Cellpose
  548. CellposeSegmentImgPlusAdvanced cellpose = new CellposeSegmentImgPlusAdvanced(settings, img);
  549. ImagePlus imgOut = cellpose.run();
  550. if(imgOut.getNChannels() > 1)
  551. imgOut.setDimensions(1, imgOut.getNChannels(), 1);
  552. imgOut.setCalibration(cal);
  554. closeImage(img);
  555. return imgOut;
  556. }
  559. /**
  560. * Detect vessels applying a median filter + DoG filter + threshold + closing filter + median filter
  561. */
  562. public ImagePlus vesselsSegmentation(ImagePlus img) {
  563. ImagePlus imgMed = medianFilter3D(img, 4, 1);
  564. ImagePlus imgDOG = dogFilter2D(imgMed, dog1Sigma1, dog1Sigma2);
  565. ImagePlus imgBin = threshold(imgDOG, vesselThMet1);
  566. if(dog2) {
  567. ImagePlus imgDOG2 = dogFilter2D(imgMed, dog2Sigma1, dog2Sigma2);
  568. ImagePlus imgBin2 = threshold(imgDOG2, vesselThMet2);
  569. new ImageCalculator().run("Max stack", imgBin, imgBin2);
  570. closeImage(imgDOG2);
  571. closeImage(imgBin2);
  572. }
  573. ImagePlus imgClose = closingFilter3D(imgBin, 8, 1);
  574. ImagePlus imgMed2 = medianFilter3D(imgClose, 1, 1);
  575. ImagePlus imgOut = fillHoles2D(imgMed2, 0, maxHoleArea);
  577. ImageInt imgLabels = new ImageLabeller().getLabels(ImageHandler.wrap(imgOut));
  578. imgLabels.setCalibration(cal);
  580. Objects3DIntPopulation pop = new Objects3DIntPopulation(imgLabels);
  581. popFilterOneZ(pop);
  582. System.out.println(pop.getNbObjects() + " vessels detected");
  583. popFilterVol(pop, minVesselVol, Double.MAX_VALUE);
  584. System.out.println(pop.getNbObjects() + " vessels remaining after size filtering");
  586. ImageHandler imgFilter = ImageHandler.wrap(img).createSameDimensions();
  587. for(Object3DInt obj: pop.getObjects3DInt())
  588. obj.drawObject(imgFilter, 255);
  589. imgFilter.setCalibration(cal);
  591. closeImage(imgMed);
  592. closeImage(imgDOG);
  593. closeImage(imgBin);
  594. closeImage(imgClose);
  595. closeImage(imgMed2);
  596. closeImage(imgOut);
  597. closeImage(imgLabels.getImagePlus());
  599. return(imgFilter.getImagePlus());
  600. }
  603. /**
  604. * Median filter using CLIJ
  605. */
  606. public ImagePlus medianFilter3D(ImagePlus img, double sizeXY, double sizeZ) {
  607. ClearCLBuffer imgCL = clij2.push(img);
  608. ClearCLBuffer imgCLMed = clij2.create(imgCL);
  609. clij2.median3DSphere(imgCL, imgCLMed, sizeXY, sizeXY, sizeZ);
  610. clij2.release(imgCL);
  611. ImagePlus imgMed = clij2.pull(imgCLMed);
  612. clij2.release(imgCLMed);
  613. return(imgMed);
  614. }
  617. /**
  618. * Difference of Gaussians using CLIJ
  619. */
  620. public ImagePlus dogFilter2D(ImagePlus img, double size1, double size2) {
  621. ClearCLBuffer imgCL = clij2.push(img);
  622. ClearCLBuffer imgCLDOG = clij2.create(imgCL);
  623. clij2.differenceOfGaussian2D(imgCL, imgCLDOG, size1, size1, size2, size2);
  624. clij2.release(imgCL);
  625. ImagePlus imgDOG = clij2.pull(imgCLDOG);
  626. clij2.release(imgCLDOG);
  627. return(imgDOG);
  628. }
  631. /**
  632. * Automatic thresholding using CLIJ2
  633. */
  634. private ImagePlus threshold(ImagePlus img, String thMed) {
  635. ClearCLBuffer imgCL = clij2.push(img);
  636. ClearCLBuffer imgCLBin = clij2.create(imgCL);
  637. clij2.automaticThreshold(imgCL, imgCLBin, thMed);
  638. ImagePlus imgBin = clij2.pull(imgCLBin);
  639. clij2.release(imgCL);
  640. clij2.release(imgCLBin);
  641. return(imgBin);
  642. }
  645. /**
  646. * Closing filtering using CLIJ2
  647. */
  648. private ImagePlus closingFilter3D(ImagePlus img, double sizeXY, double sizeZ) {
  649. ClearCLBuffer imgCL = clij2.push(img);
  650. ClearCLBuffer imgCLMax = clij2.create(imgCL);
  651. clij2.maximum3DSphere(imgCL, imgCLMax, sizeXY, sizeXY, sizeZ);
  653. ClearCLBuffer imgCLMin = clij2.create(imgCLMax);
  654. clij2.minimum3DSphere(imgCLMax, imgCLMin, sizeXY, sizeXY, sizeZ);
  655. ImagePlus imgMin = clij2.pull(imgCLMin);
  657. clij2.release(imgCL);
  658. clij2.release(imgCLMax);
  659. clij2.release(imgCLMin);
  660. return(imgMin);
  661. }
  664. /**
  665. * Fill holes with areas between the specified min and max values
  666. */
  667. private ImagePlus fillHoles2D(ImagePlus img, double minArea, double maxArea) {
  668. ImagePlus imgFill = img.duplicate();
  670. // Invert image to detect background holes
  671. IJ.setRawThreshold(imgFill, 1, 255);
  672. IJ.run(imgFill, "Convert to Mask", "background=Dark black");
  673. IJ.run(imgFill, "Invert", "stack");
  675. // Analyze particles to detect holes within the specified area range
  676. double pixArea = cal.pixelWidth*cal.pixelHeight;
  677. ParticleAnalyzer pa = new ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER, 0, new ResultsTable(), minArea/pixArea, maxArea/pixArea); // In pixels^2
  678. RoiManager rm = new RoiManager(true);
  679. pa.setRoiManager(rm);
  681. for (int s = 1; s <= imgFill.getNSlices(); s++) {
  682. imgFill.setSlice(s);
  683. pa.analyze(imgFill);
  685. // Reinvert image before filling holes
  686. IJ.run(imgFill, "Invert", "slice");
  688. // Fill the detected holes
  689. for (int i = 0; i < rm.getCount(); i++) {
  690. imgFill.setRoi(rm.getRoi(i));
  691. imgFill.setColor(Color.white);
  692. IJ.run(imgFill, "Fill", "slice");
  693. }
  694. imgFill.deleteRoi();
  695. rm.reset();
  696. }
  698. return(imgFill);
  699. }
  702. /**
  703. * Compute (inverse) 3D distance map
  704. */
  705. public ImageFloat distanceMap3D(ImagePlus img, boolean inverse) {
  706. img.setCalibration(cal);
  707. ImageFloat edt = new EDT().run(ImageHandler.wrap(img), 0, inverse, ThreadUtil.getNbCpus());
  708. return(edt);
  709. }
  712. /**
  713. * Skeletonize 3D with CLIJ2
  714. */
  715. public ImagePlus skeletonize3D(ImagePlus img) {
  716. ClearCLBuffer imgCL = clij2.push(img);
  717. ClearCLBuffer imgCLSkel = clij2.create(imgCL);
  718. new BoneJSkeletonize3D().bonejSkeletonize3D(clij2, imgCL, imgCLSkel);
  719. ImagePlus imgSkel = clij2.pull(imgCLSkel);
  720. clij2.release(imgCL);
  721. clij2.release(imgCLSkel);
  723. IJ.run(imgSkel, "8-bit","");
  724. imgSkel.setCalibration(cal);
  725. return(imgSkel);
  726. }
  729. /**
  730. * Prune skeleton branches with length smaller than threshold
  731. * https://imagej.net/plugins/analyze-skeleton/
  732. */
  733. public ImagePlus pruneSkeleton(ImagePlus image) {
  734. // Analyze skeleton
  735. AnalyzeSkeleton_ skel = new AnalyzeSkeleton_();
  736. skel.setup("", image);
  737. SkeletonResult skelResult = skel.run(AnalyzeSkeleton_.NONE, false, false, null, true, false);
  739. // Create copy of input image
  740. ImagePlus prunedImage = image.duplicate();
  741. if(skelResult.getBranches() != null) {
  742. ImageStack outStack = prunedImage.getStack();
  744. // Get graphs (one per skeleton in the image)
  745. Graph[] graphs = skelResult.getGraph();
  747. // Get list of end-points
  748. ArrayList<Point> endPoints = skelResult.getListOfEndPoints();
  750. for(Graph graph: graphs) {
  751. ArrayList<Edge> listEdges = graph.getEdges();
  753. // Go through all branches and remove branches under threshold in duplicate image
  754. for(Edge e: listEdges) {
  755. ArrayList<Point> p1 = e.getV1().getPoints();
  756. boolean v1End = endPoints.contains(p1.get(0));
  757. ArrayList<Point> p2 = e.getV2().getPoints();
  758. boolean v2End = endPoints.contains(p2.get(0));
  759. // If any of the vertices is end-point
  760. if(v1End || v2End) {
  761. if(e.getLength() < minVesselLength) { // in microns
  762. if(v1End)
  763. outStack.setVoxel(p1.get(0).x, p1.get(0).y, p1.get(0).z, 0);
  764. if(v2End)
  765. outStack.setVoxel(p2.get(0).x, p2.get(0).y, p2.get(0).z, 0);
  766. for(Point p: e.getSlabs())
  767. outStack.setVoxel(p.x, p.y, p.z, 0);
  768. }
  769. }
  770. }
  771. }
  772. }
  774. prunedImage = skeletonize3D(prunedImage);
  775. return(prunedImage);
  776. }
  779. /**
  780. * Get object in (dilated) ROI
  781. * @param dilationFactor in microns
  782. */
  783. public ImagePlus getImgInRoi(ImagePlus img, Roi roi, double dilationFactor) {
  784. ImagePlus imgClear = img.duplicate();
  785. imgClear.setRoi(dilationFactor == 0? roi : RoiEnlarger.enlarge(roi, dilationFactor/cal.pixelWidth)); // pixels
  786. IJ.run(imgClear, "Clear Outside", "stack");
  787. imgClear.setCalibration(cal);
  788. return(imgClear);
  789. }
  792. /**
  793. * Get object in (dilated) ROI
  794. */
  795. public Object3DInt getObjInRoi(ImagePlus img, Roi roi, double dilationFactor) {
  796. ImagePlus imgClear = getImgInRoi(img, roi, dilationFactor);
  797. Object3DInt obj = new Object3DInt(ImageHandler.wrap(imgClear));
  798. closeImage(imgClear);
  799. return(obj);
  800. }
  803. /**
  804. * Return population in ROI
  805. */
  806. public Objects3DIntPopulation getPopInRoi(ImagePlus img, Roi roi) throws IOException{
  807. ImagePlus imgClear = getImgInRoi(img, roi, 20);
  809. // Filter detections
  810. Objects3DIntPopulation pop = new Objects3DIntPopulation(ImageInt.wrap(imgClear));
  811. if(filterOneZ) popFilterOneZ(pop);
  812. popFilterCentroid(pop, roi);
  813. System.out.println(pop.getNbObjects() + " cells detected in ROI");
  814. popFilterVol(pop, minCellVol, maxCellVol);
  815. System.out.println(pop.getNbObjects() + " cells remaining after size filtering");
  816. pop.resetLabels();
  818. closeImage(imgClear);
  819. return(pop);
  820. }
  823. /**
  824. * Remove objects that appear in only one z-slice
  825. */
  826. private void popFilterOneZ(Objects3DIntPopulation pop) {
  827. pop.getObjects3DInt().removeIf(p -> (p.getObject3DPlanes().size() == 1));
  828. pop.resetLabels();
  829. }
  832. /**
  833. * Remove objects that do not have their centroid into a given ROI
  834. */
  835. public void popFilterCentroid(Objects3DIntPopulation pop, Roi roi) {
  836. pop.getObjects3DInt().removeIf(p -> (!roi.contains(new MeasureCentroid(p).getCentroidAsPoint().getRoundX(),
  837. new MeasureCentroid(p).getCentroidAsPoint().getRoundY())));
  838. pop.resetLabels();
  839. }
  842. /**
  843. * Remove objects with volume < min and volume > max
  844. */
  845. private void popFilterVol(Objects3DIntPopulation pop, double min, double max) {
  846. pop.getObjects3DInt().removeIf(p -> (new MeasureVolume(p).getVolumeUnit() < min) || (new MeasureVolume(p).getVolumeUnit() > max));
  847. pop.resetLabels();
  848. }
  851. /**
  852. * Remove objects with intensity < min
  853. */
  854. public void popFilterInt(Objects3DIntPopulation pop, ImagePlus img, double minInt) {
  855. ImageHandler imh = ImageHandler.wrap(img);
  856. pop.getObjects3DInt().removeIf(p -> (new MeasureIntensity(p, imh).getValueMeasurement(MeasureIntensity.INTENSITY_AVG) < minInt));
  857. pop.resetLabels();
  858. }
  861. /**
  862. * Compute distance between each cell and its closest vessel
  863. */
  864. public void computeCellsVesselsDists(Objects3DIntPopulation cellPop, ImageFloat vesselDistMapInv) {
  865. for (Object3DInt cell: cellPop.getObjects3DInt()) {
  866. double dist = vesselDistMapInv.getPixel(new MeasureCentroid​(cell).getCentroidAsPoint());
  867. cell.setCompareValue(dist);
  868. }
  869. }
  872. /**
  873. * Draw results obtained in ROI
  874. */
  875. public void drawResultsInRoi(Objects3DIntPopulation popCell, Object3DInt objVessel, Object3DInt objSkel, ImageHandler imhCell,
  876. ImageHandler imhCellDist, ImageHandler imhVessel, ImageHandler imhSkel) {
  877. // Cells
  878. popCell.drawInImage(imhCell);
  880. // Cells + vessels
  881. if (objVessel != null) {
  882. for (Object3DInt cell: popCell.getObjects3DInt()) {
  883. cell.drawObject(imhCellDist, (float)cell.getCompareValue()+10);
  884. }
  885. objVessel.drawObject(imhVessel, 255);
  886. objSkel.drawObject(imhSkel, 255);
  887. }
  888. }
  891. /**
  892. * Save results in images
  893. */
  894. public void saveCloseDrawings(ImagePlus imgCell, ImagePlus imgVessel, ImageHandler imhCell, ImageHandler imhCellDist,
  895. ImageHandler imhVessel, ImageHandler imhSkel, String outDir, String imgName) {
  896. // Cells
  897. ImagePlus[] imgColors1 = {imhCell.getImagePlus(), null, null, imgCell};
  898. ImagePlus imgObjects1 = new RGBStackMerge().mergeHyperstacks(imgColors1, true);
  899. imgObjects1.setCalibration(cal);
  900. new FileSaver(imgObjects1).saveAsTiff(outDir+imgName+"_cells.tif");
  901. closeImage(imgObjects1);
  903. // Cells + vessels
  904. if (imgVessel != null) {
  905. IJ.run(imhCellDist.getImagePlus(), "mpl-inferno", "");
  906. IJ.run(imhSkel.getImagePlus(), "Green", "");
  907. IJ.run(imhVessel.getImagePlus(), "Blue", "");
  909. ImagePlus[] imgColors2 = {imhCellDist.getImagePlus(), imhSkel.getImagePlus(), imhVessel.getImagePlus(), imgVessel};
  910. ImagePlus imgObjects2 = new RGBStackMerge().mergeHyperstacks(imgColors2, true);
  911. imgObjects2.setCalibration(cal);
  912. new FileSaver(imgObjects2).saveAsTiff(outDir+imgName+"_vessels.tif");
  913. closeImage(imgObjects2);
  914. }
  916. closeImage(imhCell.getImagePlus());
  917. closeImage(imhCellDist.getImagePlus());
  918. closeImage(imhVessel.getImagePlus());
  919. closeImage(imhSkel.getImagePlus());
  920. }
  923. /**
  924. * Write headers in results files
  925. */
  926. public void writeHeaders(String outDir, boolean computeVessel) throws IOException {
  927. // Global results
  928. FileWriter fileGlobal = new FileWriter(outDir + "globalResults.csv", false);
  929. resultsGlobal = new BufferedWriter(fileGlobal);
  930. resultsGlobal.write("Image name\tROI name\tROI area (µm²)\tROI volume (µm³)\tNb cells\tCells total volume (µm³)\t"
  931. + "Cells mean volume (µm³)\tCells volume SD (µm³)\tCells mean distance to closest neighbor (µm)\t"
  932. + "Cells distance to closest neighbor SD (µm)\tCells mean distance to "+nbNei+" closest neighbors (µm)\t"
  933. + "Cells distance to "+nbNei+" closest neighbors SD (µm)"+"\tCells mean of max distance to "+nbNei+" neighbors (µm)\t"
  934. + "Cells SD of max distance to "+nbNei+" neighbors (µm)");
  935. if (computeGFunction) resultsGlobal.write("\tCells G-function SDI\tCells G-function AUC difference");
  936. if (computeVessel) resultsGlobal.write("\tCells mean distance to closest vessel (µm)\tVessels total volume (µm³)"
  937. + "\tVessels total length (µm)\tBranches mean length (µm)\tNb branches\tNb junctions\tVessels mean diameter (µm)\tVessels diameter SD (µm)");
  938. resultsGlobal.write("\n");
  939. resultsGlobal.flush();
  941. // Detailed results
  942. FileWriter fileDetail = new FileWriter(outDir +"cellsResults.csv", false);
  943. resultsDetail = new BufferedWriter(fileDetail);
  944. resultsDetail.write("Image name\tROI name\tCell ID\tCell volume (µm³)\tCell distance to closest neighbor (µm)\t"
  945. + "Cell mean distance to "+nbNei+" closest neighbors (µm)\tCell max distance to "+nbNei+" closest neighbors (µm)");
  946. if(computeVessel) resultsDetail.write("\tCell distance to closest vessel (µm)\tClosest vessel diameter (µm)");
  947. resultsDetail.write("\n");
  948. resultsDetail.flush();
  949. }
  952. /**
  953. * Compute parameters and save them in results files
  954. * @throws java.io.IOException
  955. */
  956. public void writeResultsInRoi(Objects3DIntPopulation popCellRoi, Object3DInt objSkelRoiDil, Object3DInt objSkelRoi,
  957. ImageFloat distMap, ImagePlus imgCell, Roi roi, double vesselVol, String outDir, String imgName) throws IOException {
  959. DescriptiveStatistics cellsVolume = new DescriptiveStatistics();
  960. DescriptiveStatistics cellsClosestVesselDist = new DescriptiveStatistics();
  961. DescriptiveStatistics cellsClosestNeighborDist = new DescriptiveStatistics();
  962. DescriptiveStatistics cellsNeighborsMeanDist = new DescriptiveStatistics();
  963. DescriptiveStatistics cellsNeighborsMaxDist = new DescriptiveStatistics();
  965. // CELLS INDIVIDUAL STATISTICS
  966. print("Computing cells individual statistics...");
  967. MeasurePopulationDistance allCellsDists = new MeasurePopulationDistance​(popCellRoi, popCellRoi, Double.POSITIVE_INFINITY, "DistCenterCenterUnit");
  968. for (Object3DInt cell: popCellRoi.getObjects3DInt()) {
  969. double cellVol = new MeasureVolume(cell).getVolumeUnit();
  970. cellsVolume.addValue(cellVol);
  971. resultsDetail.write(imgName+"\t"+roi.getName()+"\t"+cell.getLabel()+"\t"+cellVol);
  972. resultsDetail.flush();
  974. if(popCellRoi.getNbObjects() == 1) {
  975. resultsDetail.write("\t"+Double.NaN+"\t"+Double.NaN+"\t"+Double.NaN);
  976. resultsDetail.flush();
  977. } else {
  978. List<PairObjects3DInt> cellCellsDists = allCellsDists.getPairsObject1(cell.getLabel(), true);
  979. double closestNeighborDist = cellCellsDists.get(1).getPairValue();
  980. cellsClosestNeighborDist.addValue(closestNeighborDist);
  982. DescriptiveStatistics cellNeighborsDists = new DescriptiveStatistics();
  983. for (int d=1; d <= Math.min(nbNei, popCellRoi.getNbObjects()-1); d++)
  984. cellNeighborsDists.addValue(cellCellsDists.get(d).getPairValue());
  986. double closestNeighborsMeanDist = cellNeighborsDists.getMean();
  987. cellsNeighborsMeanDist.addValue(closestNeighborsMeanDist);
  988. double closestNeighborsMaxDist = cellNeighborsDists.getMax();
  989. cellsNeighborsMaxDist.addValue(closestNeighborsMaxDist);
  991. resultsDetail.write("\t"+closestNeighborDist+"\t"+closestNeighborsMeanDist+"\t"+closestNeighborsMaxDist);
  992. resultsDetail.flush();
  993. }
  995. cellsClosestVesselDist.addValue(cell.getCompareValue());
  996. if (objSkelRoiDil != null) {
  997. double diam = 2*distMap.getPixel(new Measure2Distance(cell, objSkelRoiDil).getBorder2Pix());
  998. resultsDetail.write("\t"+cell.getCompareValue()+"\t"+diam);
  999. resultsDetail.flush();
  1000. }
  1002. resultsDetail.write("\n");
  1003. resultsDetail.flush();
  1004. }
  1006. // CELLS GLOBAL STATISTICS
  1007. print("Computing cells global statistics...");
  1008. double[] roiParams = roiParams(roi, imgCell);
  1009. resultsGlobal.write(imgName+"\t"+roi.getName()+"\t"+roiParams[0]+"\t"+roiParams[1]+"\t"+popCellRoi.getNbObjects()+"\t"+
  1010. cellsVolume.getSum()+"\t"+cellsVolume.getMean()+"\t"+cellsVolume.getStandardDeviation()+"\t"+
  1011. cellsClosestNeighborDist.getMean()+"\t"+cellsClosestNeighborDist.getStandardDeviation()+"\t"+
  1012. cellsNeighborsMeanDist.getMean()+"\t"+cellsNeighborsMeanDist.getStandardDeviation()+"\t"+
  1013. cellsNeighborsMaxDist.getMean()+"\t"+cellsNeighborsMaxDist.getStandardDeviation());
  1015. if (computeGFunction) {
  1016. if(popCellRoi.getNbObjects() <= 1) {
  1017. resultsGlobal.write("\t"+Double.NaN+"\t"+Double.NaN);
  1018. resultsGlobal.flush();
  1019. } else {
  1020. System.out.println("Computing G-function-related spatial distribution index...");
  1021. Object3DInt mask = roiMask(imgCell, roi);
  1022. double minDist = Math.pow(3*minCellVol/(4*Math.PI*pixelVol), 1/3) * 2; // min distance = 2 * min cell radius (in pixels)
  1023. String plotName = outDir + imgName + "_" + roi.getName() + "_gfunction.tif";
  1024. double[] res = computeSdiG(popCellRoi, mask, imgCell, minDist, nbRandomSamples, plotName);
  1025. resultsGlobal.write("\t"+res[0]+"\t"+res[1]);
  1026. resultsGlobal.flush();
  1027. }
  1028. }
  1030. // VESSELS STATISTICS
  1031. if(objSkelRoi == null) {
  1032. resultsGlobal.write("\t0\t0\t0\t0\t0\t0\t0\t0");
  1033. resultsGlobal.flush();
  1034. } else {
  1035. print("Computing vessels statistics...");
  1036. ImageHandler imhSkel = ImageHandler.wrap(imgCell).createSameDimensions();
  1037. objSkelRoi.drawObject(imhSkel, 255);
  1038. IJ.run(imhSkel.getImagePlus(), "8-bit","");
  1040. AnalyzeSkeleton_ analyzeSkeleton = new AnalyzeSkeleton_();
  1041. analyzeSkeleton.setup("", imhSkel.getImagePlus());
  1042. SkeletonResult skelResult = analyzeSkeleton.run(AnalyzeSkeleton_.NONE, false, false, null, true, false);
  1043. closeImage(imhSkel.getImagePlus());
  1045. if(skelResult.getBranches() == null) {
  1046. resultsGlobal.write("\t0\t0\t0\t0\t0\t0\t0\t0");
  1047. resultsGlobal.flush();
  1048. } else {
  1049. double[] branchLengths = skelResult.getAverageBranchLength();
  1050. int[] branchNumbers = skelResult.getBranches();
  1051. double totalLength = 0;
  1052. for (int i = 0; i < branchNumbers.length; i++)
  1053. totalLength += branchNumbers[i] * branchLengths[i];
  1055. DescriptiveStatistics diams = new DescriptiveStatistics();
  1056. for (Point pt: skelResult.getListOfSlabVoxels())
  1057. diams.addValue(2*distMap.getPixel(pt.x, pt.y, pt.z));
  1059. resultsGlobal.write("\t"+cellsClosestVesselDist.getMean()+"\t"+vesselVol+"\t"+totalLength+"\t"+StatUtils.mean(branchLengths)+"\t"+
  1060. IntStream.of(branchNumbers).sum()+"\t"+IntStream.of(skelResult.getJunctions()).sum()+"\t"+
  1061. diams.getMean()+"\t"+diams.getStandardDeviation());
  1062. resultsGlobal.flush();
  1063. }
  1064. }
  1066. resultsGlobal.write("\n");
  1067. resultsGlobal.flush();
  1068. }
  1071. /**
  1072. * Compute ROI area and volume
  1073. */
  1074. public double[] roiParams(Roi roi, ImagePlus img) {
  1075. PolygonRoi poly = new PolygonRoi(roi.getFloatPolygon(), Roi.FREEROI);
  1076. poly.setLocation(0, 0);
  1077. img.setRoi(poly);
  1079. ResultsTable rt = new ResultsTable();
  1080. Analyzer analyzer = new Analyzer(img, Analyzer.AREA, rt);
  1081. analyzer.measure();
  1082. double area = rt.getValue("Area", 0);
  1083. double vol = area * img.getNSlices() * cal.pixelDepth;
  1084. double[] params = {area, vol};
  1085. return(params);
  1086. }
  1089. // Get ROI as a 3D object
  1090. public Object3DInt roiMask(ImagePlus img, Roi roi) {
  1091. ImagePlus imgMask = img.duplicate();
  1092. imgMask.setRoi(roi);
  1093. for (int n = 1; n <= imgMask.getNSlices(); n++) {
  1094. imgMask.setSlice(n);
  1095. IJ.run(imgMask, "Fill", "stack");
  1096. IJ.run(imgMask, "Clear Outside", "stack");
  1097. }
  1098. imgMask.setCalibration(cal);
  1100. Object3DInt mask = new Object3DInt​(ImageHandler.wrap(imgMask));
  1101. closeImage(imgMask);
  1102. return(mask);
  1103. }
  1106. /**
  1107. * Compute G-function-related Spatial Distribution Index of cells population in a ROI
  1108. * https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000853
  1109. */
  1110. public double[] computeSdiG(Objects3DIntPopulation popInt, Object3DInt roiInt, ImagePlus img, double distHardCore, int numRandomSamples, String plotName) {
  1111. // Convert Object3DInt & Objects3DIntPopulation objects into Object3D & Objects3DPopulation objects
  1112. ImageHandler imhRoi = ImageHandler.wrap(img).createSameDimensions();
  1113. roiInt.drawObject(imhRoi, 1);
  1114. Object3D roi = new Objects3DPopulation(imhRoi).getObject(0);
  1115. closeImage(imhRoi.getImagePlus());
  1116. ImageHandler imhPop = ImageHandler.wrap(img).createSameDimensions();
  1117. popInt.drawInImage(imhPop);
  1118. Objects3DPopulation pop = new Objects3DPopulation(imhPop);
  1119. closeImage(imhPop.getImagePlus());
  1121. // Define spatial descriptor and model
  1122. SpatialDescriptor spatialDesc = new G_Function();
  1123. SpatialModel spatialModel = new SpatialRandomHardCore(pop.getNbObjects(), distHardCore, roi); // average diameter of a cell in pixels
  1124. SpatialStatistics spatialStatistics = new SpatialStatistics(spatialDesc, spatialModel, numRandomSamples, pop); // nb of samples (randomized organizations simulated to compare with the spatial organization of the cells)
  1125. spatialStatistics.setEnvelope(0.05); // 2.5-97.5% envelope error
  1126. spatialStatistics.setVerbose(false);
  1127. double sdiG = spatialStatistics.getSdi();
  1128. double areaG = spatialStatistics.getAUCDifference();
  1130. Plot plotG = spatialStatistics.getPlot();
  1131. plotG.draw();
  1132. plotG.addLabel(0.05, 0.1, "SDI = " + String.format("%.5f", sdiG));
  1133. plotG.addLabel(0.05, 0.15, "Area = " + String.format("%.5f", areaG));
  1134. ImagePlus imgPlot = plotG.getImagePlus();
  1135. FileSaver plotSave = new FileSaver(imgPlot);
  1136. plotSave.saveAsTiff(plotName);
  1137. closeImage(imgPlot);
  1138. double[] results = {sdiG, areaG};
  1139. return(results);
  1140. }
  1143. /**
  1144. * Close results files
  1145. */
  1146. public void closeResults() throws IOException {
  1147. resultsGlobal.close();
  1148. resultsDetail.close();
  1149. }
  1151. }

Tools.java at commit a84b038, no license · at the source

Overview

Authors: Naomie Guille1, Héloïse Monnet1, Tristan Hourcade1, Philippe Mailly1, Martine Cohen‐Salmon1, Anne‐Cécile Boulay1
ORCID iDs: Naomie Guille, Héloïse Monnet, Tristan Hourcade, Martine Cohen‐Salmon, Anne‐Cécile Boulay
  1. Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, Université Paris Sciences et Lettres (PSL), Paris, France
Institutions: Centre National de la Recherche Scientifique (France); Inserm (France); Collège de France (France); Université Paris Sciences et Lettres (France); Centre Interdisciplinaire de Recherche en Biologie (France)
Journal: International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience, volume 86, issue 5, article e70161
Dates: received 10 December 2025; accepted 2 July 2026; published online 28 July 2026; in print August 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1002/jdn.70161 · PMID 42517543 · PMCID PMC13411183 · OpenAlex W7171572316
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), mouse (organism)
Methods: Statistics, Machine learning, fMRI & imaging
Keywords: astrocyte, blood vessel, cell density, cell distribution, cortical development, oligodendrocyte
MeSH: Blood Vessels*, Neuroglia*, Somatosensory Cortex*, Age Factors, Animals, Animals, Newborn, Astrocytes, Female, Gene Expression Regulation, Developmental, Male, Mice, Mice, Inbred C57BL, Neurodevelopment, SOX9 Transcription Factor, SOXE Transcription Factors (* major topic)
Topic: Neurogenesis and neuroplasticity mechanisms (Developmental Neuroscience, Neuroscience), according to OpenAlex
Funding: Université PSL; France Sclérose en Plaques; ANR (ANR-23-CE16-0030); Fondation pour la Recherche Médicale (EQU202303016292)
Citations: not cited yet (Europe PMC); 52 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above, with 4 matches between paragraphs and lines of code.

orion-cirb/VeCell

License: none: the authors keep all their rights
State: the link answers, verified on 26 September 2026
Evidence: files inventoried
Commit: a84b0387457d39c2cd91b448712089fbbf9201c0, 10 December 2025
Languages: Java (8), Jupyter (2)
Size: 23 files, 10 scripts
Software Heritage: not archived
Found in: the text, “Image Analysis”
Holds: README, 2 notebooks
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Cellpose (2 files), Matplotlib (2 files), NumPy (2 files), pandas (2 files)
Availability: 1 check, the latest on 26 September 2026: the link answers
  • 26 September 2026: the link answers
11 files
At the source: github.com/orion-cirb/VeCell

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 10 scripts, each with its path and the digest of its content;
  • 4 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • it says that the data are available on request

Read it in the paper: doi.org/10.1002/jdn.70161.

Versions

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Version 3, 28 September 2026

  • Publisher: n/a → Wiley

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 6 keywords, 15 MeSH terms, 4 funders, 51 references.

Cite

This paper

Guille, N., Monnet, H., Hourcade, T., Mailly, P., Cohen‐Salmon, M., & Boulay, A. (2026). Spatio-Temporal Dynamics of Macroglial Cell Organization and Proximity to Blood Vessels During Postnatal Development. International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience, 86(5), e70161. https://doi.org/10.1002/jdn.70161

BibTeX

@article{guille2026spatio,
author = {Guille, Naomie and Monnet, Héloïse and Hourcade, Tristan and Mailly, Philippe and Cohen‐Salmon, Martine and Boulay, Anne‐Cécile},
title = {{Spatio-Temporal Dynamics of Macroglial Cell Organization and Proximity to Blood Vessels During Postnatal Development}},
journal = {International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience},
year = {2026},
month = aug,
volume = {86},
number = {5},
pages = {e70161},
publisher = {Wiley},
issn = {0736-5748},
doi = {10.1002/jdn.70161},
url = {https://doi.org/10.1002/jdn.70161},
pmid = {42517543},
pmcid = {PMC13411183}
}

RIS

TY - JOUR
AU - Guille, Naomie
AU - Monnet, Héloïse
AU - Hourcade, Tristan
AU - Mailly, Philippe
AU - Cohen‐Salmon, Martine
AU - Boulay, Anne‐Cécile
TI - Spatio-Temporal Dynamics of Macroglial Cell Organization and Proximity to Blood Vessels During Postnatal Development
T2 - International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience
J2 - Int J Dev Neurosci
PY - 2026
DA - 2026/08/01
VL - 86
IS - 5
SP - e70161
SN - 0736-5748
PB - Wiley
DO - 10.1002/jdn.70161
UR - https://doi.org/10.1002/jdn.70161
LA - en
ER -

CSL-JSON

{
"id": "10.1002/jdn.70161",
"type": "article-journal",
"title": "Spatio-Temporal Dynamics of Macroglial Cell Organization and Proximity to Blood Vessels During Postnatal Development",
"container-title": "International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience",
"author": [
{
"family": "Guille",
"given": "Naomie"
},
{
"family": "Monnet",
"given": "Héloïse"
},
{
"family": "Hourcade",
"given": "Tristan"
},
{
"family": "Mailly",
"given": "Philippe"
},
{
"family": "Cohen‐Salmon",
"given": "Martine"
},
{
"family": "Boulay",
"given": "Anne‐Cécile"
}
],
"container-title-short": "Int J Dev Neurosci",
"volume": "86",
"issue": "5",
"page": "e70161",
"DOI": "10.1002/jdn.70161",
"PMID": "42517543",
"PMCID": "PMC13411183",
"ISSN": "0736-5748",
"publisher": "Wiley",
"URL": "https://doi.org/10.1002/jdn.70161",
"language": "en",
"issued": {
"date-parts": [
[
2026,
8,
1
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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