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Title Quantifying DNA Damage in Comet Assay Images Using Neural Networks
  • S.J.K. Dhinsey, T. Greenshaw, C.P. Welsch
    The University of Liverpool, Liverpool, United Kingdom
  • J.L. Parsons
    Cancer Research Centre, University of Liverpool, Liverpool, United Kingdom
  • C.P. Welsch
    Cockcroft Institute, Warrington, Cheshire, United Kingdom
Abstract Proton therapy for cancer treatment is a rapidly growing field and increasing evidence suggests it induces more complex DNA damage than photon therapy. Accurate comparison between the two treatments requires quantification of the DNA damage the cause, which can be assessed using the Comet Assay. The program outlined here is based on neural network architecture and aims to speed up analysis of Comet Assay images and provide accurate, quantifiable assessment of the DNA damage levels apparent in individual cells. The Comet Assay is an established technique in which DNA fragments are spread out under the influence of an electric field, producing a comet-like object. The elongation and intensity of the comet tail (consisting of DNA fragments) indicate the level of damage incurred. Many methods to measure this damage exist, using a variety of algorithms. However, these can be time consuming, so often only a small fraction of the comets available in an image are analysed. The automatic analysis presented in this contribution aims to improve this. To supplement the training and testing of the network, a Monte Carlo model will also be presented to create simulated comet assay images.
Funding This work was supported by the STFC Liverpool Centre for Doctoral Training on Data Intensive Science (LIV. DAT) under grant agreement ST/P006752/1.
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Conference IPAC2021
Series International Particle Accelerator Conference (12th)
Location Campinas, SP, Brazil
Date 24-28 May 2021
Publisher JACoW Publishing, Geneva, Switzerland
Editorial Board Liu Lin (LNLS, Campinas, Brazil); John M. Byrd (ANL, Lemont, IL, USA); Regis Neuenschwander (LNLS, Campinas, Brazil); Renan Picoreti (LNLS, Campinas, Brazil); Volker R. W. Schaa (GSI, Darmstadt, Germany)
Online ISBN 978-3-95450-214-1
Online ISSN 2673-5490
Received 19 May 2021
Accepted 09 June 2021
Issue Date 16 August 2021
DOI doi:10.18429/JACoW-IPAC2021-MOPAB411
Pages 1233-1236
Creative Commons CC logoPublished by JACoW Publishing under the terms of the Creative Commons Attribution 3.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI.