Method for measurement of collagen monomer orientation in fluorescence microscopy

Rodrigo P. Alzola, José Francisco Delpiano, Anuj Gajjar, Rickard Stureborg, Seyed Mohammad Siadat, Jeffrey W. Ruberti, Charles A. Dimarzio

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Collagen is one of the most important proteins in mammals, conforming most animal tissues. This work explores how a basic collagen monomer unit is visualized using fluorescence microscopy and how its spatial orientation is determined. Defining the orientation of collagen monomers is not a trivial problem, as the particle has a weak contrast and is relatively small. Possible attach fluorescence tags for contrast, but the size is still a problem for detecting orientation using fluorescence microscopy. This document presents a simulation of the visualization of collagen monomers and two methods for detecting monomer and classifying its orientation. A modify Gabor filter set, and an automatic classifier, trained by convolutional neuronal network (CNN), were used. By evaluating the performance of these two approaches compare to human observation, our results show that it is possible to determine the location and orientation of a single monomer with fluorescence microscopy. These findings can contribute to understanding collagen elements as collagen fibril.

Original languageEnglish
Title of host publicationThree-Dimensional and Multidimensional Microscopy
Subtitle of host publicationImage Acquisition and Processing XXVIII
EditorsThomas G. Brown, Tony Wilson, Laura Waller
PublisherSPIE
Pages19
ISBN (Electronic)9781510641334
ISBN (Print)9781510641334
DOIs
StatePublished - 4 Mar 2021
EventThree-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVIII 2021 - Virtual, Online, United States
Duration: 6 Mar 202111 Mar 2021

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11649
ISSN (Print)1605-7422

Conference

ConferenceThree-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVIII 2021
Country/TerritoryUnited States
CityVirtual, Online
Period6/03/2111/03/21

Bibliographical note

Funding Information:
JR, CD, and SMS gratefully acknowledge partial funding from the United States National Institutes of Health under grant number 1R21EY029167-01. J.D. thankfully acknowledges funding from Project FONDECYT 1180685 (Comision Nacional de Investigacion Cientifica y Tecnologica Chile), the Advanced Center of Electrical and Electronic Engineering AC3E (CONICYT/FB0008) and from Fondo de Ayuda a la Investigacion (FAI), Universidad de los Andes.

Publisher Copyright:
© 2021 Copyright SPIE.

Keywords

  • Collagen
  • computer vision
  • fluorescence microscopy
  • machine learning

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