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Title: Cardiac X-ray context sensitive imaging
Author: Kengyelics, Stephen Mark
ISNI:       0000 0004 6421 1632
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2017
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Over the past two decades there have been significant advances in the technology used in the field of cardiac X-ray imaging with the advent of fully digital X-ray detectors. However, the means by which the advantages of this technology are implemented at a systems level remain basic. Most modern cardiac X-ray imaging systems employ feedback control to maintain an adequate average output signal level to the X-ray detector based on the attenuation properties of the patient. This approach is not necessarily optimal over the range of clinical imaging tasks for an individual, or over an anthropomorphically heterogeneous population. Within this thesis methods are presented for extracting dynamic real-time information from within cardiac image sequences that are suitable for incorporation in automatic dose rate control systems that regulate their output based on clinically relevant image quality metrics. A framework is proposed that combines image quality metrics for contrast and noise on a per image frame basis to provide an overall indicator of image acceptability. These metrics are compared to the performance of experienced clinical observers. The methods presented have a wider applicability to other X-ray procedures that use dynamic imaging of blood vessels made visible by the use of contrast agents.
Supervisor: Davies, Andrew ; Magee, Derek Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available