A set of computational tools are presented that allow convenient calculation of x-ray spectra, selection of elemental and compound filters, and calculation of beam quality characteristics, such as half-value layer, mR/mAs, and fluence per unit exposure. The TASMIP model of Boone and Seibert is adapted to a library of high-level language (Matlab™) functions and shown to agree with experimental measurements across a wide range of kVp and beam filtration. Modeling of beam filtration is facilitated by a convenient, extensible database of mass and mass-energy attenuation coefficients compiled from the National Institute of Standards and Technology. The functions and database were integrated in a graphical user interface and made available online at http://www.aip.org/epaps/epaps.html. The functionality of the toolset and potential for investigation of imaging system optimization was illustrated in theoretical calculations of imaging performance across a broad range of kVp, filter material type, and filter thickness for direct and indirect-detection flat-panel imagers. The calculations reveal a number of nontrivial effects in the energy response of such detectors that may not have been guessed from simple K-edge filter techniques, and point to a variety of compelling hypotheses regarding choice of beam filtration that warrant future investigation.

Spektr: A computational tool for x-ray spectral analysis and imaging system optimization

A study was conducted to compare physical and clinical system performance in digital chest radiography. Four digital X-ray modalities, two storage-phosphor based systems and two generations of a CCD-based system, were evaluated in terms of both their imaging properties (determination of presampling MTF and DQE) and clinical image quality (grading of the reproduction of anatomical details of 23 healthy volunteers using both absolute and relative visual grading analysis). One of the two storage-phosphor systems performed best in both evaluations and the first generation of the CCD-based system was rated worst; however, the other two systems were ranked differently with the two methods. The newest CCD-based system yielded a higher clinical image quality than the second storage-phosphor system, although the latter presented a DQE substantially higher than the former. The results show that clinical performance cannot be predicted from determinations of DQE alone, and that a system with lower DQE, under the quantum-saturated conditions in chest radiography, can outperform a system with higher DQE if the image processing used on the former is more effective in presenting the information in the image to the radiologist.

Comparison of visual grading analysis and determination of detective quantum efficiency for evaluating system performance in digital chest radiography.

Solid-state, flat-panel, digital radiography detectors and their physical imaging characteristics.

There are many ways in which imaging systems can be evaluated. The aim of the present paper is to provide an overview of a number of selected approaches to evaluating imaging systems, often encountered by the medical physicist, and discuss their validity and reliability. Specifically, it will cover (i) characterisation of an imaging system in terms of its detective quantum efficiency using linear-systems analysis; (ii) attempts to calculate relevant measures directly in images using the Rose model and the pixel signal-to-noise ratio; (iii) task-based methods incorporating human observers such as receiver-operating characteristics and (iv) visual grading-based methods using experienced radiologists as observers.

Evaluating imaging systems: practical applications

The purpose of this study was to perform a complete evaluation of three pieces of clinical digital mammography equipment. Image quality was assessed by performing physical characterization and contrast-detail (CD) analysis. We considered three different FFDM systems: a computed radiography unit (Fuji "FCR 5000 MA") and two flat-panel units, the indirect conversion a-Si based GE "Senographe 2000D" and the direct conversion a-Si based IMS "Giotto Image MD." The physical characterization was estimated by measuring the MTF, NNPS, and DQE of the detectors with no antiscatter grid and over the clinical range of exposures. The CD analysis was performed using a CDMAM 3.4 phantom and custom software designed for automatic computation of the contrast-detail curves. The physical characterization of the three digital systems confirms the excellent MTF properties of the direct conversion flat-panel detector (FPD). We performed a relative standard deviation (RSD) analysis, for investigating the different components of the noise presented by the three systems. It turned out that the two FPDs show a significant additive component, whereas for the CR system the statistical noise is dominant. The multiplicative factor is a minor constituent for all the systems. The two FPDs demonstrate better DQE, with respect to the CR system, for exposures higher than 70 microGy. The CD analysis indicated that the three systems are not statistically different for detail objects with a diameter greater than 0.3 mm. However, the IMS system showed a statistically significant different response for details smaller than 0.3 mm. In this case, the poor response of the a-Se detector could be attributed to its high-frequency noise characteristics, since its MTF, NEQ, and DQE are not inferior to those of the other systems. The CD results were independent of exposure level, within the investigated clinical range. We observed slight variations in the CD results, due to the changes in the visualization parameters (window/level and magnification factor). This suggests that radiologists would benefit from viewing images using varied window/level and magnification.

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Comparison of different commercial FFDM units by means of physical characterization and contrast-detail analysis

In most imaging detectors, the modulation transfer function (MTF) is regarded as a good parameter to describe spatial resolution. This is undoubtedly valid for visual observation. However, the detectability of a detail is essentially a matter of signal-to-noise ratio, which is not accounted for by the MTF. In x-ray imaging, signal-to-noise ratio in the image is generally limited by incident photons statistics, often larger than readout noises. Therefore, the MTF of the detector applies to both signal and noise, and does not impair the image content. Contrast can easily be restored by image processing without altering the signal-to-noise ratio. However, a number of effects may alter very differently noise and signal: (i) If the MTF significantly extends beyond half the sampling frequency, the aliasing introduced by spatial sampling can severely enhance the noise and cancel the benefit of the good signal transfer. This is illustrated by synthetic images which simulate the response of imagers with different MTFs to the same test pattern in the presence of quantum noise. (ii) Parallax and blurring by the x-ray spot size or motion are shown to degrade the transfer properties of signal, but do not affect the quantum noise; they must be treated separately. Contrary to the x-ray converter MTF, parallax directly impacts the detective quantum efficiency (DQE). Finally, it is shown that only the detective quantum efficiency can reliably describe the spatial resolution of an x-ray imaging detector in the presence of noise, parallax and blurring.

Jean-Pierre Moy

Papers

Signal-to-noise ratio and spatial resolution in x-ray electronic imagers: is the MTF a relevant parameter?