A novel method for contrast-to-noise ratio (CNR) evaluation of digital mammography detectors.
ABSTRACT The purpose of this study was to test a new, simple method of evaluating the contrast-to-noise ratio (CNR) over the entire image field of a digital detector and to compare different mammography systems. Images were taken under clinical exposure conditions for a range of simulated breast thicknesses using poly(methyl methacrylate) (PMMA). At each PMMA thickness, a second image which included an additional 0.2-mm Al sheet was also acquired. Image processing software was used to calculate the CNR in multiple regions of interest (ROI) covering the entire area of the detector in order to obtain a 'CNR image'. Five detector types were evaluated, two CsI-alphaSi (GE Healthcare) flat panel systems, one alphaSe (Hologic) flat panel system and a two generations of scanning photon counting digital detectors (Sectra). Flat panel detectors exhibit better CNR uniformity compared with the first-generation scanning photon counting detector in terms of mean pixel value variation. However, significant improvement in CNR uniformity was observed for the next-generation scanning detector. The method proposed produces a map of the CNR and a measurement of uniformity throughout the entire image field of the detector. The application of this method enables quality control measurement of individual detectors and a comparison of detectors using different technologies.
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ABSTRACT: The comparative performance of mammographic X-ray systems that use different anode/filter combinations has been assessed for screen-film and digital imaging. Monte Carlo techniques have been used to calculate average glandular dose as well as contrast and signal-to-noise ratio for imaging two test details. Five anode/filter combinations have been studied to establish the potential for dose saving or image quality improvement. For screen-film mammography, it was found that little benefit is gained by changing from a standard 28 kV molybdenum/molybdenum spectrum for breasts up to 6 cm thick. For thicker breasts, where the tube potential for the standard technique might be increased, 20% improvement in contrast can be achieved without dose penalty using molybdenum/rhodium or rhodium/rhodium spectra, whereas dose savings of more than 50% can be attained whilst maintaining contrast using tungsten/rhodium or rhodium/aluminium spectra. In digital mammography, a molybdenum/molybdenum spectrum delivers the lowest dose for a 2 cm breast, but gives the highest dose for thicker breasts. Tungsten/rhodium or rhodium/aluminium spectra provide the lowest doses at greater thicknesses. It is concluded that for screen-film mammography, molybdenum/molybdenum is the spectrum of choice for all but the thickest or most glandular breasts. In digital mammography, an alternative spectrum is preferable for breasts thicker than 2 cm.British Journal of Radiology 11/2000; 73(874):1056-67. · 1.22 Impact Factor
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ABSTRACT: To review the evidence demonstrating that early detection of breast cancer substantially decreases death from the disease, and to demonstrate that the significant change in the outcome of breast cancer patients results from a combination of early detection and surgical removal of breast cancer, as treatment of the late stage disease provides little impact on ultimate outcome. Review results of the randomized controlled trials of mammographic screening and the published results of service screening. Both randomized controlled trials and service screening, when performed properly, provide unequivocal evidence demonstrating that arresting the disease in its preclinically detectable phase has significant impact on outcome. Primary emphasis should be upon preventing breast cancer from developing to metastatic disease. Numerous scientific trials have repeatedly and convincingly confirmed that breast cancer is progressive rather than a systemic disease from its inception. Progression of breast cancer can be arrested through detection and treatment at an early phase. The time at which disease progression is arrested has significant impact on clinical outcome, making mammographic screening a key factor in the control of breast cancer.International Journal of Gynecology & Obstetrics 10/2003; 82(3):319-26. · 1.84 Impact Factor
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ABSTRACT: A method of measuring the image quality of medical imaging equipment is considered within the framework of statistical decision theory. In this approach, images are regarded as random vectors and image quality is defined in the context of the image information available for performing a specified detection or discrimination task. The approach provides a means of measuring image quality, as related to the detection of an image detail of interest, without reference to the actual physical mechanisms involved in image formation and without separate measurements of signal transfer characteristics or image noise. The measurement does not, however, consider deterministic errors in the image; they need a separate evaluation for imaging modalities where they are of concern. The detectability of an image detail can be expressed in terms of the ideal observer's signal-to-noise ratio (SNR) at the decision level. Often a good approximation to this SNR can be obtained by employing sub-optimal observers, whose performance correlates well with the performance of human observers as well. In this paper the measurement of SNR is based on implementing algorithmic realizations of specified observers and analysing their responses while actually performing a specified detection task of interest. Three observers are considered: the ideal prewhitening matched filter, the non-prewhitening matched filter, and the DC-suppressing non-prewhitening matched filter. The construction of the ideal observer requires an impractical amount of data and computing, except for the most simple imaging situations. Therefore, the utilization of sub-optimal observers is advised and their performance in detecting a specified signal is discussed. Measurement of noise and SNR has been extended to include temporally varying images and dynamic imaging systems.Physics in Medicine and Biology 02/1993; 38(1):71-92. · 2.70 Impact Factor