A Perceptual Colour Separation Methodology for Automated Quantification of Ki67 and Hematoxylin Stained Digital Histopathology Images

dc.contributor.advisorDony, Robert
dc.contributor.authorMorreale, Peter
dc.date.accessioned2018-05-09T15:10:46Z
dc.date.available2018-05-09T15:10:46Z
dc.date.copyright2018-04
dc.date.created2018-04-23
dc.date.issued2018-05-09
dc.degree.departmentSchool of Engineeringen_US
dc.degree.grantorUniversity of Guelphen_US
dc.degree.nameMaster of Applied Scienceen_US
dc.degree.programmeEngineeringen_US
dc.description.abstractThis thesis is focussed on the development of a colour separation methodology for quantification of histopathology stains Ki67 and hematoxylin. Traditional methods require tedious manual evaluations prone to inter and intra-observer variability due to inherent subjectivity. Automatic algorithms have been proposed as the solution to manual challenges, however many algorithms are sensitive to wide staining variability common among histopathology images. This thesis proposes a perceptual colour separation framework that models colour information in a way that mimics the human visual systems ability to identify colour content. It is an automatic framework that was evaluated against 30 manually labelled canine mammary TMA core images. The average difference between manual and automatic PI estimates was 3.25%, with a Kappa similarity statistic of 0.86 across four Ki67 cut-off levels, and a linear correlation coefficient of 0.93. Validation studies show the colour separation framework achieves robust results across various Ki67 staining levels.en_US
dc.identifier.urihttp://hdl.handle.net/10214/13021
dc.language.isoenen_US
dc.publisherUniversity of Guelphen_US
dc.rights.licenseAll items in the Atrium are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectImage Processingen_US
dc.subjectKi67en_US
dc.subjectHematoxylinen_US
dc.subjectHistopathologyen_US
dc.subjectColour separationen_US
dc.subjectStain separationen_US
dc.subjectdigital image analysisen_US
dc.titleA Perceptual Colour Separation Methodology for Automated Quantification of Ki67 and Hematoxylin Stained Digital Histopathology Imagesen_US
dc.typeThesisen_US

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