Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338888
Title: An investigation of the imaging performance of CCD based X-ray detectors for digital mammography
Author: Ho, Ian
ISNI:       0000 0001 3579 2982
Awarding Body: University of London
Current Institution: University College London (University of London)
Date of Award: 1996
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Abstract:
This thesis describes the imaging performance of a prototype digital mammography system based upon charge coupled devices (CCDs). The imaging performance of these detectors is dependent upon the configuration of the detector. In this thesis the performance of 14 different detector configurations are studied for use in digital mammography. Experimental evaluations of factors which affect the performance of imaging systems such as quantum detection efficiency, dynamic range, modulation transfer function (MTF(f)) and Noise power spectrum (NPS) were performed. The use of spatial frequency dependent detective quantum efficiency DQE(f) to characterise the detectors in terms of signal to noise ratio transfer is described. It is shown that direct interactions of x-rays in the CCD act to reduce DQE(f) at high spatial frequencies and severely impair the detectors ability to detect small objects (250|im in diameter). The use of a sufficient thickness of fibre optic faceplate to couple the phosphor layer to the CCD is shown to remove these interactions and shows a corresponding increase in DQE(f) (at higher spatial frequencies) and the detector's ability to image smaller objects A subjective comparison of images of a breast phantom shows that images of superior quality were obtained with the prototype system compared with images produced using a conventional film-screen system, for a slight increase in dose. Improvements to the system and detector design are presented and will act to try to produce the same image quality for equivalent doses used in conventional mammography.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.338888  DOI: Not available
Keywords: Pattern recognition & image processing
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