Jul 01, 2020

Public workspaceSPARC_Duke_PelotGrill_OT2-OD025340_PigVagusNerve_Morphology

DOI
dx.doi.org/10.17504/protocols.io.6bvhan6
  • Nicole A. Pelot1,
  • Gabriel B. Goldhagen1,
  • Jake E. Cariello1,
  • Warren M. Grill1
  • 1Duke University
  • SPARC
    Tech. support email: info@neuinfo.org
Nicole A Pelot
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DOI: dx.doi.org/10.17504/protocols.io.6bvhan6
Protocol Citation: Nicole A. Pelot, Gabriel B. Goldhagen, Jake E. Cariello, Warren M. Grill 2020. SPARC_Duke_PelotGrill_OT2-OD025340_PigVagusNerve_Morphology. protocols.io https://dx.doi.org/10.17504/protocols.io.6bvhan6
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: August 10, 2019
Last Modified: July 01, 2020
Protocol Integer ID: 26709
Keywords: Vagus nerve, nerve morphology, pig vagus nerve, endoneurium, perineurium, epineurium, fascicles, image segmentation
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Abstract
The protocol describes image segmentation and image analysis methods to quantify pig vagus nerve morphology from Masson's trichrome-stained nerve cross sections.
Materials
  • Nikon's NIS Elements
  • Matlab
Image Segmentation
Image Segmentation
We used Nikon's NIS Elements software (v5.02.01, Build 1270) to segment pig vagus nerve micrographs stained with Masson's trichrome using the General Analysis RGB tool.
For each image, we selected preprocessing steps, such as smoothing and sharpening.
For each image, we selected ranges of hues, saturations, and intensities to values that identify the endoneurium (fascicles) and different values to identify the entirety of the nerve.
For each image, we selected postprocessing steps, such as setting a minimum size criterion (eliminate small off-target regions), smoothing, cleaning, closing, and filling holes.
We made manual adjustments as needed, including manual deletion of off-target regions and filling of target areas that had not been captured.
We converted the binary segmented image into “Graticule Masks”, binary images saved as TIFs.
Image Analysis
Image Analysis
We imported the TIFs into Matlab and generated a data structure of the x and y coordinates of the pixels for each closed boundary of the loaded binary images using the bwboundaries function.
We scaled the pixel coordinates to microns using the segmented scale bar.
We calculated cross-sectional area of each fascicle and nerve using Matlab’s polyarea. Effective diameter (for a nerve or fascicle) is the diameter of the circle that has the same cross-sectional area as the raw trace.