Quantitative analysis of digital substraction angiograms
Occlusive vascular disease (e.g. arteriosclerosis) is a major and growing health problem worldwide. New drug treatments - as opposed to conventional bypass surgery - have attracted much research interest but a key obstacle here is the lack of any objective methodology for assessing the effectiveness...
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ndltd-bl.uk-oai-ethos.bl.uk-4890762015-03-20T05:13:29ZQuantitative analysis of digital substraction angiogramsZou, Ping2008Occlusive vascular disease (e.g. arteriosclerosis) is a major and growing health problem worldwide. New drug treatments - as opposed to conventional bypass surgery - have attracted much research interest but a key obstacle here is the lack of any objective methodology for assessing the effectiveness of these treatments (before and after studies). The clinical data sources are digital subtraction angiograms (DSAs) which are a routine assessment of patients presenting with symptoms of occlusive vascular disease. Novel image processing algorithms are required to analyse these DS A images which are of low quality though of high spatial resolution and likely to contain complex vascular networks. Ultimately, we aim to model the haemodynamic capacity of the patient's vascular system using the geometric information extracted from DSAs.616.1307548University of Sheffieldhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.489076Electronic Thesis or Dissertation |
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616.1307548 Zou, Ping Quantitative analysis of digital substraction angiograms |
description |
Occlusive vascular disease (e.g. arteriosclerosis) is a major and growing health problem worldwide. New drug treatments - as opposed to conventional bypass surgery - have attracted much research interest but a key obstacle here is the lack of any objective methodology for assessing the effectiveness of these treatments (before and after studies). The clinical data sources are digital subtraction angiograms (DSAs) which are a routine assessment of patients presenting with symptoms of occlusive vascular disease. Novel image processing algorithms are required to analyse these DS A images which are of low quality though of high spatial resolution and likely to contain complex vascular networks. Ultimately, we aim to model the haemodynamic capacity of the patient's vascular system using the geometric information extracted from DSAs. |
author |
Zou, Ping |
author_facet |
Zou, Ping |
author_sort |
Zou, Ping |
title |
Quantitative analysis of digital substraction angiograms |
title_short |
Quantitative analysis of digital substraction angiograms |
title_full |
Quantitative analysis of digital substraction angiograms |
title_fullStr |
Quantitative analysis of digital substraction angiograms |
title_full_unstemmed |
Quantitative analysis of digital substraction angiograms |
title_sort |
quantitative analysis of digital substraction angiograms |
publisher |
University of Sheffield |
publishDate |
2008 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.489076 |
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AT zouping quantitativeanalysisofdigitalsubstractionangiograms |
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1716789543879835648 |