Quantitative analysis of digital substraction angiograms

• Main Author: Zou, Ping
• Published: University of Sheffield 2008
• Subjects: 616.1307548
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.489076

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.