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.
- SourceAvailable from: Eduardo Borba Neves
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- "The PMMA and the Al attenuation is equivalent to a 10 mm thickness plate of PMMA (Young et al 2006b). Some authors suggested that the CNR is the parameter indicated to assess the image quality in digital mammography (Young et al 2006c, Samei et al 2005, Baldelli et al 2009). The CNR for a particular set of clinical exposure parameters was determined using a 20 mm side square of Al foil, 99% of purity and 0.2 mm thickness, placed over a 20 mm thickness PMMA plate of 24 cm × 30 cm (Al-PMMA phantom). "
ABSTRACT: In many countries, computed radiography (CR) systems represent the majority of equipment used in digital mammography. This study presents a method for optimizing image quality and dose in CR mammography of patients with breast thicknesses between 45 and 75 mm. Initially, clinical images of 67 patients (group 1) were analyzed by three experienced radiologists, reporting about anatomical structures, noise and contrast in low and high pixel value areas, and image sharpness and contrast. Exposure parameters (kV, mAs and target/filter combination) used in the examinations of these patients were reproduced to determine the contrast-to-noise ratio (CNR) and mean glandular dose (MGD). The parameters were also used to radiograph a CDMAM (version 3.4) phantom (Artinis Medical Systems, The Netherlands) for image threshold contrast evaluation. After that, different breast thicknesses were simulated with polymethylmethacrylate layers and various sets of exposure parameters were used in order to determine optimal radiographic parameters. For each simulated breast thickness, optimal beam quality was defined as giving a target CNR to reach the threshold contrast of CDMAM images for acceptable MGD. These results were used for adjustments in the automatic exposure control (AEC) by the maintenance team. Using optimized exposure parameters, clinical images of 63 patients (group 2) were evaluated as described above. Threshold contrast, CNR and MGD for such exposure parameters were also determined. Results showed that the proposed optimization method was effective for all breast thicknesses studied in phantoms. The best result was found for breasts of 75 mm. While in group 1 there was no detection of the 0.1 mm critical diameter detail with threshold contrast below 23%, after the optimization, detection occurred in 47.6% of the images. There was also an average MGD reduction of 7.5%. The clinical image quality criteria were attended in 91.7% for all breast thicknesses evaluated in both patient groups. Finally, this study also concluded that the use of the AEC of the x-ray unit based on the constant dose to the detector may bring some difficulties to CR systems to operate under optimal conditions. More studies must be performed, so that the compatibility between systems and optimization methodologies can be evaluated, as well as this optimization method. Most methods are developed for phantoms, so comparative studies including clinical images must be developed.Physics in Medicine and Biology 09/2013; 58(18):6565-6583. DOI:10.1088/0031-9155/58/18/6565 · 2.92 Impact Factor
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ABSTRACT: A method of eliminating pixelization effect from en face optical coherence tomography (OCT) image when a fiber bundle is used as an OCT imaging probe is presented. We have demonstrated that applying a histogram equalization process before performing a weighted-averaged Gaussian smoothing filter to the original lower gray level intensity based image not only removes the structural artifact of the bundle but also enhances the image quality with minimum blurring of object's image features. The measured contrast-to-noise ratio (CNR) for an image of the US Air Force test target was 14.7dB (4.9dB), after (before) image processing. In addition, by performing the spatial frequency analysis based on two-dimensional discrete Fourier transform (2-D DFT), we were able to observe that the periodic intensity peaks induced by the regularly arrayed structure of the fiber bundle can be efficiently suppressed by 41.0dB for the first nearby side lobe as well as to obtain the precise physical spacing information of the fiber grid. The proposed combined method can also be used as a straight forward image processing tool for any imaging system utilizing fiber bundle as a high-resolution imager.Optics Express 03/2010; 18(7):7427-39. DOI:10.1364/OE.18.007427 · 3.53 Impact Factor
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ABSTRACT: This work examines the use of a detectability index to control an Automatic Exposure Control (AEC) system for an amorphous-Selenium digital mammography detector. The default AEC mode for the system was evaluated using homogeneous poly(methyl methacrylate) (PMMA) plates of thickness 20, 40, 60 and 70 mm to find the tube potential and anode/filter settings selected by the system. Detectability index (d') using a non-prewhitened model observer with eye filter (NPWE) was calculated for these beam qualities as a function of air kerma at the detector. AEC settings were calculated that gave constant d' as a function of beam quality for a homogeneous background; a target d' was used that ensured the system passed the achievable image quality criterion for the 0.1 mm diameter disc in the European Guidelines. Threshold gold thickness was measured using the CDMAM test object as a function of beam quality for the AEC mode, which held pixel value (PV) constant, and for the constant d' mode. Threshold gold thickness for the 0.1 mm disc increased by a factor of 2.18 for the constant PV mode, while constant d' mode held threshold gold thickness constant to within 7% and signal-difference-to-noise-ratio (SdNR) constant to within 5%. The constant d' settings derived for homogeneous images were then applied to a phantom with a structured background. Threshold gold thickness for the 0.13 mm disc increased by a factor of 1.90 for the constant PV mode, while constant d' mode held threshold gold thickness constant within 38% for 0.13 mm disk.Medical Imaging 2011: Physics of Medical Imaging; 02/2011