Application of machine learning techniques for the quantification of myelin ultra-structure in transmission electron micrographs of the rat spinal cord
department or school: Science, Faculty of
department or school: Zoology, Department of
data provider: DSpace
degree campus: UBCV
creator: Holmes, Nathan
issued: 2023-11-23T19:43:32Z
issued: 2023
related degree: Master of Science - MSc
degree grantor: University of British Columbia
description: Assessing the morphology of myelin in transmission electron micrograph (TEM) images is an important research tool for studying certain neuropathologies and neuroregeneration. Additionally, TEM can be used to validate the accuracy of other methods of measuring the state of myelin as it allows direct visualization of myelin ultra-structure. Often this requires laborious manual quantification of TEM micrographs to extract useful morphological data, especially in cases where the feature of interest is not commonly measured such that software is not commercially available to aid in quantification. A recent study produced by our lab involved comparing measurements of myelin based on magnetic resonance imaging (MRI) T2 relaxation with TEM images in conditions of healthy and degenerating myelin in the rat spinal cord following a dorsal column transection injury. The MRI T2 techniques can quantify the amount of water trapped between layers of the myelin sheaths, as opposed to water in other spaces in healthy tissue. However, what the MRI T2 measurement was actually corresponding to in degenerating tissue was unknown. The TEM portion of this analysis involved manually tracing the area of the myelin sheath, and thresholding the image to separate intact myelin from vacuous spaces occurring in the myelin as it degenerates. This made it possible to determine that the MRI T2 technique only measures to the quantity of intact myelin in degenerating tissue. This thesis uses the TEM images and the manually quantified intact myelin measurements as data-sets for training machine learning approaches to automate this task. Three approaches are trained and evaluated: a k-nearest neighbour (KNN) approach based on natural clustering of image histograms, a standard SegNet deep-learning artificial neural network, and a more generic dense prediction artificial neural network featuring skip-connections to preserve low level data. The KNN approach was found to be completely unsuitable for the tas…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/86658
note: Application of Machine Learning Techniques for the Quantification of Myelin Ultra-structure inTransmission Electron Micrographs of the Rat Spinal CordbyNathan HolmesB.S., The University of British Columbia, 2011B.C.S., The University of British Columbia, 2017A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMaster of Sciencein THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES(Zoology)THE UNIVERSITY OF BRITISH COLUMBIA(Vancouver)November 2023© Nathan Holmes, 2023The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled:Application of Machine Learning Techniques for the Quantification of Myelin Ultra-structure inTransmission Electron Micrographs of the Rat Spinal Cordsubmitted by Nathan Holmes in partial fulfilment of the requirements forthe degree of Master of Sciencein ZoologyExamining Committee:Wolfram Tetzlaff, Professor, Zoology, UBCSupervisor Piotr Kozlowski, Professor, Radiology, UBCSupervisory Committee Member,Doug Altshuler, Professor, Zoology, UBCAdditional ExaminerAdditional Supervisory Committee Members:Vanessa Auld, Professor, Zoology, UBCSupervisory Committee MemberiiAbstractAssessing the morphology of myelin in transmission electron micrograph (TEM) images is an important research tool for studying certain neuropathologies and neuroregeneration. Additionally, TEM can be used to validate the accuracy of other methods of measuring the state of myelin as it allows direct visualization of myelin ultra-structure. Often this requires laborious manual quantificationof TEM micrographs to extract useful morphological data, especially in cases where the feature of interest is not commonly measured such that software is not commercially available to aid in quantification.A recent study produced by our lab involved comparing measurements of myelin based on magnetic resonance imaging (MRI) T2 relaxation with TEM images in conditions of health…
has type: Thesis/Dissertation
date issued: 2024-05
is shown at: 10.14288/1.0437872
language: eng
degree discipline: Zoology
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Tetzlaff, Wolfram
type: Text
identifier URI: http://hdl.handle.net/2429/86658