{
  "paper": "rozak-2026-neurovascular-dl",
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    "orphans": [
      {
        "uid": "results-010",
        "section": "results",
        "text": "The Dice, precision, recall, mean surface distance, and HD95 distance for the vascular ( A ) and neuron ( B ) channels.",
        "stats": [],
        "panels": [
          "fig3a",
          "fig3b"
        ]
      },
      {
        "uid": "results-014",
        "section": "results",
        "text": "( A ) Raw images of the vascular channel with the neuron channel subtracted to facilitate vessel visualization.",
        "stats": [],
        "panels": [
          "fig4a"
        ]
      },
      {
        "uid": "results-017",
        "section": "results",
        "text": "( B ) Ground truth segmentation masks for the vasculature were generated by a rater who utilized ilastik-assisted manual segmentation.",
        "stats": [],
        "panels": [
          "fig4b"
        ]
      },
      {
        "uid": "results-018",
        "section": "results",
        "text": "( C ) Ilastik predictions generated via a random forest model.",
        "stats": [],
        "panels": [
          "fig4c"
        ]
      },
      {
        "uid": "results-019",
        "section": "results",
        "text": "( D ) Binary segmentation masks generated by an ensemble of 3D UNet models.",
        "stats": [],
        "panels": [
          "fig4d"
        ]
      },
      {
        "uid": "results-020",
        "section": "results",
        "text": "( E ) Binary segmentation masks generated by an ensemble of 3D UNETR models.",
        "stats": [],
        "panels": [
          "fig4e"
        ]
      },
      {
        "uid": "results-029",
        "section": "results",
        "text": "Across > 100,000 simulations, the fit of the estimated radius following rescaling against the simulated radius had an R 2 value of 0.68. Figure 5B presents a heatmap of the estimated radius post-scaling vs. simulated radius, across different vertices of vessel centerlines, highlighting the ability of our pipeline to estimate vascular radii accurately.",
        "stats": [],
        "panels": [
          "fig5b"
        ]
      },
      {
        "uid": "results-032",
        "section": "results",
        "text": "( A ) An image in the plane orthogonal to the local tangent to a capillary with the detected boundary (in blue) and with the estimated radius of 2.28 \u03bcm.",
        "stats": [],
        "panels": [
          "fig5a"
        ]
      },
      {
        "uid": "results-034",
        "section": "results",
        "text": "( B ) The plot shows correspondence between the estimated radius following scaling and the simulated level of scaling.",
        "stats": [],
        "panels": [
          "fig5b"
        ]
      },
      {
        "uid": "results-035",
        "section": "results",
        "text": "( C ) An image in the plane orthogonal to the local tangent of a capillary with the detected boundary (in blue) and with the estimated radius of 3.65 \u03bcm.",
        "stats": [],
        "panels": [
          "fig5c"
        ]
      },
      {
        "uid": "results-037",
        "section": "results",
        "text": "( D ) The estimated % change in the vessel\u2019s radius after the addition of varying levels of Gaussian noise, demonstrating the robustness of the radius estimated to noise.",
        "stats": [],
        "panels": [
          "fig5d"
        ]
      },
      {
        "uid": "results-043",
        "section": "results",
        "text": "As the amount of averaging increased, the uncertainty on the diameter of the beads decreased, and our estimate of the bead\u2019s diameter converged upon the manufacturer\u2019s Coulter counter-based specifications (7.32\u00b10.27 \u03bcm), as tabulated below in Table 1 .",
        "stats": [],
        "panels": [
          "table1"
        ]
      },
      {
        "uid": "results-044",
        "section": "results",
        "text": "Table 1. Bead diameter estimates.",
        "stats": [],
        "panels": [
          "table1"
        ]
      },
      {
        "uid": "results-049",
        "section": "results",
        "text": "To highlight the ability of the pipeline to detect vessels that significantly change their radius after stimulation, Figure 6A shows the standard deviation of the average radii on each vessel segment during baseline frames for three mice.",
        "stats": [],
        "panels": [
          "fig6a"
        ]
      },
      {
        "uid": "results-051",
        "section": "results",
        "text": "We examined the average change in the vascular radius of each vessel segment after vs. before photostimulation ( Figure 6B ), with even finer spatial patterns detected by analyzing the vertex-wise radius changes ( Figure 6C ).",
        "stats": [],
        "panels": [
          "fig6b",
          "fig6c"
        ]
      },
      {
        "uid": "results-052",
        "section": "results",
        "text": "The vascular diameter changes were related to the distance from the vessel\u2019s surface to the closest labeled pyramidal neuron at each vertex of the centerline ( Figure 6D ).",
        "stats": [],
        "panels": [
          "fig6d"
        ]
      },
      {
        "uid": "results-057",
        "section": "results",
        "text": "Table 2. S1FL vascular network morphological properties.",
        "stats": [],
        "panels": [
          "table2"
        ]
      },
      {
        "uid": "results-059",
        "section": "results",
        "text": "( A ) Baseline variability in vessel diameter estimated by the standard deviation of each vessel\u2019s mean radius across baseline time frames.",
        "stats": [],
        "panels": [
          "table2a"
        ]
      },
      {
        "uid": "results-060",
        "section": "results",
        "text": "( B ) Mean change in the vessel radius induced by optogenetic stimulation.",
        "stats": [],
        "panels": [
          "table2b"
        ]
      },
      {
        "uid": "results-061",
        "section": "results",
        "text": "( C ) Mean change in the vertexwise radius, allowing the visualization of heterogeneity of radius changes within each vessel.",
        "stats": [],
        "panels": [
          "table2c"
        ]
      },
      {
        "uid": "results-062",
        "section": "results",
        "text": "( D ) Distance from each vertex to the closest pyramidal neuron.",
        "stats": [],
        "panels": [
          "table2d"
        ]
      },
      {
        "uid": "results-067",
        "section": "results",
        "text": "( B ) Estimates of the vertex-wise radius obtained along each of the three vessels\u2019 centrelines, before and after stimulation.",
        "stats": [],
        "panels": [
          "fig7b"
        ]
      },
      {
        "uid": "results-068",
        "section": "results",
        "text": "( C ) Vertex-wise radii changes in response to optogenetic stimulation.",
        "stats": [],
        "panels": [
          "fig7c"
        ]
      },
      {
        "uid": "results-069",
        "section": "results",
        "text": "( D ).",
        "stats": [],
        "panels": [
          "fig7d"
        ]
      },
      {
        "uid": "results-074",
        "section": "results",
        "text": "The morphometric properties of the responders, under different stimulation conditions, are listed in Table 3 .",
        "stats": [],
        "panels": [
          "table3"
        ]
      },
      {
        "uid": "results-081",
        "section": "results",
        "text": "Table 3. Details of responder (\u0394 R >2 * \u03c3R baseline ) vessels.",
        "stats": [],
        "panels": [
          "table3"
        ]
      },
      {
        "uid": "results-084",
        "section": "results",
        "text": "( C ) Probability density function of constrictions and dilations for the 4.3 mW/mm 2 photostimulation.",
        "stats": [],
        "panels": [
          "table3c"
        ]
      },
      {
        "uid": "results-085",
        "section": "results",
        "text": "( D ) Changes to capillary radii are displayed in relation to the closest pyramidal neurons.",
        "stats": [],
        "panels": [
          "table3d"
        ]
      },
      {
        "uid": "results-087",
        "section": "results",
        "text": "( E ) Mean cortical depth of responding capillaries showed a tendency for dilators to be closer to the surface and for constrictors to be deeper in the tissue.",
        "stats": [],
        "panels": [
          "table3e"
        ]
      },
      {
        "uid": "results-094",
        "section": "results",
        "text": "For constrictions, 458 nm photostimulations led to \u20131.39\u00b11.51 \u03bcm radius changes with 1.1 m W m m 2 \\begin{document}$\\frac{mW}{mm^{2}}$\\end{document} and \u20131.20\u00b11.13 \u03bcm radius changes with 4.3 m W m m 2 \\begin{document}$\\frac{mW}{mm^{2}}$\\end{document} (p=4.4e-3), whereas 552 nm photostimulation induced \u20130.37\u00b10.30 \u03bcm radius changes with 4.3 m W m m 2 \\begin{document}$\\frac{mW}{mm^{2}}$\\end{document} of power, which was smaller than the 458 nm induced responses (p=0.02).",
        "stats": [
          "p=4.4e-3",
          "p=0.02"
        ],
        "panels": []
      },
      {
        "uid": "results-102",
        "section": "results",
        "text": "( A ) Graph representation of a vascular network of 425 vascular segments from a single image stack.",
        "stats": [],
        "panels": [
          "fig9a"
        ]
      },
      {
        "uid": "results-108",
        "section": "results",
        "text": "There was a significant increase (p=0.03) in the capillary network efficiency post 458 nm light at 4.3 mW/mm 2 , when compared to that following the control green illumination.",
        "stats": [
          "p=0.03"
        ],
        "panels": []
      },
      {
        "uid": "discussion-063",
        "section": "discussion",
        "text": "Example slices of the segmentation results are shown in Appendix 1\u2014figure 10 .",
        "stats": [],
        "panels": [
          "fig10"
        ]
      },
      {
        "uid": "discussion-068",
        "section": "discussion",
        "text": "Visualizations of the two graphs are shown in Appendix 1\u2014figure 11 .",
        "stats": [],
        "panels": [
          "fig11"
        ]
      },
      {
        "uid": "discussion-077",
        "section": "discussion",
        "text": "Our vascular segmentation model generalized well to C57BL/6J mouse and Fischer rat data, as well as to Thy1-ChR2 light-sheet fluorescence microscopy images gathered on an UltraMicroscope Blaze lightsheet fluorescence microscope (Miltenyi Biotech) ( Appendix 1\u2014figures 12 and 13 and Supplementary file 3, table 3 ).",
        "stats": [],
        "panels": [
          "fig12",
          "table3"
        ]
      },
      {
        "uid": "discussion-085",
        "section": "discussion",
        "text": "Additionally, alternative definitions of responding vessels may be useful depending on the end goal of a study (e.g. selecting a threshold for the radius change based on a percentage change from the baseline level: Appendix 1\u2014figure 14 for capillary changes above 10% of the baseline radius).",
        "stats": [],
        "panels": [
          "fig14"
        ]
      },
      {
        "uid": "captions-003",
        "section": "captions",
        "text": "The emitted light passes through the objective, is reflected off the FV30-NDM690 dichroic mirror, and passes through a 650 nm barrier filter before reaching a 570 nm long pass filter (LPF) separating emitted light from EYFP and TexasRed, which respectively pass through 495\u2013540 nm and 575\u2013630 nm barrier filters to be collected via GaAsP detectors. === Figure 2 === Figure 2. Computational analysis pipeline.",
        "stats": [],
        "panels": [
          "fig2"
        ]
      },
      {
        "uid": "captions-061",
        "section": "captions",
        "text": "There was a significant increase (p=0.03) in the capillary network efficiency post 458 nm light at 4.3 mW/mm 2 , when compared to that following the control green illumination.",
        "stats": [
          "p=0.03"
        ],
        "panels": []
      },
      {
        "uid": "tables-001",
        "section": "tables",
        "text": "Table 1. Bead diameter estimates.",
        "stats": [],
        "panels": [
          "table1"
        ]
      },
      {
        "uid": "tables-002",
        "section": "tables",
        "text": "Number of orthogonal planes Number of spokes per plane Mean diameter estimate (\u03bcm) 1 3 7.54\u00b10.68 2 4 7.44\u00b10.51 4 12 7.34\u00b10.38 10 36 7.34\u00b10.32 Table 2. S1FL vascular network morphological properties.",
        "stats": [],
        "panels": [
          "table2"
        ]
      }
    ]
  }
}