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dc.contributor.advisorQahwaji, Rami S.R.
dc.contributor.advisorIpson, Stanley S.
dc.contributor.authorHammadi, Shumoos T.H.*
dc.date.accessioned2019-03-26T16:39:14Z
dc.date.available2019-03-26T16:39:14Z
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/10454/16924
dc.description.abstractDiabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the corneal epithelium nerve structures and the corneal endothelial cell can assist early diagnosis of this disease and other corneal diseases, which can lead to visual impairment and then to blindness. In this thesis, fully-automated segmentation and quantification algorithms for processing and analysing sub-basal epithelium nerves and endothelial cells are proposed for early diagnosis of diabetic neuropathy in Corneal Confocal Microscopy (CCM) images. Firstly, a fully automatic nerve segmentation system for corneal confocal microscope images is proposed. The performance of the proposed system is evaluated against manually traced images with an execution time of the prototype is 13 seconds. Secondly, an automatic corneal nerve registration system is proposed. The main aim of this system is to produce a new informative corneal image that contains structural and functional information. Thirdly, an automated real-time system, termed the Corneal Endothelium Analysis System (CEAS) is developed and applied for the segmentation of endothelial cells in images of human cornea obtained by In Vivo CCM. The performance of the proposed CEAS system was tested against manually traced images with an execution time of only 6 seconds per image. Finally, the results obtained from all the proposed approaches have been evaluated and validated by an expert advisory board from two institutes, they are the Division of Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar and the Manchester Royal Eye Hospital, Centre for Endocrinology and Diabetes, UK.en_US
dc.language.isoenen_US
dc.rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.eng
dc.subjectMedical imagingen_US
dc.subjectDiabetic peripheral neuropathyen_US
dc.subjectCorneal confocal microscopyen_US
dc.subjectAutomatic nerve segmentationen_US
dc.subjectCorneal sub-basal epitheliumen_US
dc.subjectAutomatic nerve segmentationen_US
dc.subjectAnisotropic diffusion filteringen_US
dc.subjectCorneal endothelial cellsen_US
dc.subjectAutomatic cell segmentationen_US
dc.subjectFast Fourier transformen_US
dc.subjectWatershed transformationen_US
dc.titleNovel medical imaging technologies for processing epithelium and endothelium layers in corneal confocal images. Developing automated segmentation and quantification algorithms for processing sub-basal epithelium nerves and endothelial cells for early diagnosis of diabetic neuropathy in corneal confocal microscope imagesen_US
dc.type.qualificationleveldoctoralen_US
dc.publisher.institutionUniversity of Bradfordeng
dc.publisher.departmentSchool of Electrical Engineering and Computer Scienceen_US
dc.typeThesiseng
dc.type.qualificationnamePhDen_US
dc.date.awarded2018
refterms.dateFOA2019-03-26T16:39:14Z


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