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|Title:||Modelling the imaging performance and low contrast detectability in digital mammography|
|Authors:||Σπυροπούλου, Βασιλική Α.|
Καλύβας, Νεκτάριος Ι.
Μιχαήλ, Χρήστος Μ.
Παναγιωτάκης, Γεώργιος Σ.
|Contributors:||Κανδαράκης, Ιωάννης Σ.|
|Item type:||Journal article|
|Keywords:||X-ray detectors;Simulation methods and programs;Ανιχνευτές ακτίνων-Χ;Μέθοδοι και προγράμματα προσομοίωσης|
|Date of availability:||18-Jan-2015|
|Publisher:||IOP Publishing Ltd|
|Abstract:||A digital x-ray mammography is a modern method for the early detection of breast cancer. The quality of a mammography image depends on various factors, the detector structure and performance being of primary importance. The aim of this work was to develop an analytical model simulating the imaging performance of a new commercially available digital mammography detector. This was achieved within the framework of the linear cascaded systems (LCS) theory. System analysis has allowed the estimation of important image quality metrics such as the Modulation Transfer Function (MTF), the Noise Power Spectrum (NPS) and the Detective Quantum Efficiency (DQE). The detector was an indirect detection system consisting of a large area, 100μm thick, CsI:TI scintillator coupled to an active matrix array of amorphous silicon (a-Si:H) photodiodes combined with thin film transistors (TFT). Pixel size was 100μm, while the active pixel dimension was 70μm. MTF and DQE data were calculated for air kerma conditions of 25, 53, 67 μGy using a 28 kVp Mo-Mo x-ray spectrum. The theoretical results were compared with published experimental data. The deviation between the theoretical and experimental MTF curves was less than 4%, while the DQE differences were found at an acceptable level. The model was also used to estimate system's capability to detect low contrast objects in the breast. It was estimated that, in the breast gland, low contrast structures larger than 1.4mm can be adequately identified by the above system.|
|Description:||Part of 4th International Conference on Imaging Technologies in Biomedical Sciences|
|Citation:||Spyropoulou, V., Kalyvas, N., Gaitanis, A., Michail, C., Panayiotakis, G., et al. (June 2009). Modelling the imaging performance and low contrast detectability in digital mammography. Journal of Instrumentation. 4(6). pp. 1-5. IOP Publishing Ltd. Available from: http://iopscience.iop.org|
|Journal:||Journal of Instrumentation|
|Type of Journal:||With a review process (peer review)|
|Access scheme:||Publicly accessible|
|License:||Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες|
|Appears in Collections:||Δημοσιεύσεις|
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