Solid-state fluoroscopic imager for high-resolution angiography: parallel-cascaded linear systems analysis.

The performance of a high-resolution charge coupled device-based full-field digital mammography imager was analysed using a mathematical framework based on an adaptation of cascaded linear systems theory described by other investigators. This work has been conducted in order to understand the impact of various design parameters on the physical performance characteristics of the imager. Specifically, the effect of pixel size, scintillator thickness and packing density, x-ray spectra, air kerma, dark current, charge integration time, and pixel fill-factor on the frequency dependent detective quantum efficiency was studied using a charge-coupled device as a reference platform. The imaging system was modelled as a series of physical processes with gain and spatial spreading. For each stage, the signal and noise power spectra were computed and propagated through the imaging chain as inputs to subsequent stages. Good agreement between experimental and theoretical predictions was obtained for various x-ray spectral conditions that were investigated. The modulation transfer function, MTF(f) and detective quantum efficiency DQE(f) characteristics obtained in this study are encouraging and comparable to other digital mammography systems. The results of this study strongly suggest the feasibility of large area scintillator-based digital mammography imagers with pixel sizes below 100 µm.

The ability to improve visualization of structural information in digital radiography without increasing radiation exposures requires improved image quality across all spatial frequencies, especially at high frequencies. The detective quantum efficiency (DQE) as a function of spatial frequency quantifies image quality given by an x-ray detector. We present a method of increasing DQE at high spatial frequencies by improving the modulation transfer function (MTF) and reducing noise aliasing. The Apodized Aperature Pixel (AAP) design uses a detector with micro-elements to synthesize desired pixels and provide higher DQE than conventional detector designs. A cascaded system analysis (CSA) that incorporates x-ray interactions is used for comparison of the theoretical MTF, noise power spectrum (NPS), and DQE. Signal and noise transfer through the converter material is shown to consist of correlated an uncorrelated terms. The AAP design was shown to improve the DQE of both material types that have predominantly correlated transfer (such as CsI) and predominantly uncorrelated transfer (such as Se). Improvement in the MTF by 50% and the DQE by 100% at the sampling cut-off frequency is obtained when uncorrelated transfer is prevalent through the converter material. Optimizing high-frequency DQE results in improved image contrast and visualization of small structures and fine-detail.

Current flat-panel detectors either directly convert x-ray energy to electronic charge or use indirect conversion with an intermediate optical process. The purpose of this work was to compare direct and indirect detectors in terms of their modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). Measurements were made on three flat-panel detectors, Philips Digital Diagnost, GE Revolution XQ/i, and Hologic Direct-Ray DR1000 using the IEC-defined RQA5 (approximately 75 kVp, 21 mm Al) and RQA9 (approximately 120 kVp, 40 mm Al) radiographic techniques. The presampled MTF of the systems was measured using an edge method (Samei et al., Med Phys 25:102, 1998). The NPS of the systems was determined for a range of exposure levels by 2D Fourier analysis of uniformly exposed radiographs (Flynn and Samei, Med Phys 26:1612, 1999). The ideal signal-to-noise ratio per exposure for each system was estimated using a semi-empirical x-ray model. The DQE, reported only at the RQA5 technique, was assessed from the measured MTF, NPS, exposure, and the ideal signal-to-noise ratio. For the direct system, the MTF was found to be significantly higher than that for the indirect systems and very close to an ideal function associated with the detector pixel size. The NPS for the direct system was found to be constant in relation to frequency. The DQE results reflected expected differences based on the absorption efficiency of the different detector materials. Using RQA5 and 0.3 mR exposure, the measured DQE values at spatial frequencies of 0.15 mm-1 and 2.5 mm-1 were 64% and 14% for the XQ/i system and 35% and 19% for DR-1000. Using RQA5 and the averages at all exposures, the corresponding values were 58% and 13% for the XQ/i system and 36% and 19% for DR-1000.

Background/Objectives: In digital radiography imaging, dual-layer flat-panel detectors (DFDs), in which two flat-panel detector layers are stacked with a minimal distance between the layers and appropriate alignment, are commonly used in material decompositions as dual-energy applications with a single x-ray exposure. DFDs also enable more efficient use of incident photons, resulting in x-ray images with improved noise power spectrum (NPS) and detection quantum efficiency (DQE) performances as single-energy applications. Purpose: Although the development of DFD systems for material decomposition applications is actively underway, there is a lack of research on whether single-energy applications of DFD can achieve better performance than the single-layer case. In this paper, we experimentally observe the DFD performance in terms of the modulation transfer function (MTF), NPS, and DQE with discussions. Methods: Using prototypes of DFD, we experimentally measure the MTF, NPS, and DQE of the convex combination of the images acquired from the upper and lower detector layers of DFD. To optimize DFD performance, a two-step image registration is performed, where subpixel registration based on the maximum amplitude response to the transform based on the Fourier shift theorem and an affine transformation using cubic interpolation are adopted. The DFD performance is analyzed and discussed through extensive experiments for various scintillator thicknesses, x-ray beam conditions, and incident doses. Results: Under the RQA 9 beam conditions of 2.7 μGy dose, the DFD with the upper and lower scintillator thicknesses of 0.5 mm could achieve a zero-frequency DQE of 75%, compared to 56% when using a single-layer detector. This implies that the DFD using 75 % of the incident dose of a single-layer detector can provide the same signal-to-noise ratio as a single-layer detector. Conclusions: In single-energy radiography imaging, DFD can provide better NPS and DQE performances than the case of the single-layer detector, especially at relatively high x-ray energies, which enables low-dose imaging.

Photon counting detectors (PCDs) are an emerging technology with applications in spectral and low-dose radiographic and tomographic imaging. This paper develops an analytical model of PCD imaging performance, including the system gain, modulation transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). A cascaded systems analysis model describing the propagation of quanta through the imaging chain was developed. The model was validated in comparison to the physical performance of a silicon-strip PCD implemented on an experimental imaging bench. The signal response, MTF, and NPS were measured and compared to theory as a function of exposure conditions (70 kVp, 1-7 mA), detector threshold, and readout mode (i.e., the option for coincidence detection). The model sheds new light on the dependence of spatial resolution, charge sharing, and additive noise effects on threshold selection and was used to investigate the factors governing PCD performance, including the fundamental advantages and limitations of PCDs in comparison to energy-integrating detectors (EIDs) in the linear regime for which pulse pileup can be ignored. The detector exhibited highly linear mean signal response across the system operating range and agreed well with theoretical prediction, as did the system MTF and NPS. The DQE analyzed as a function of kilovolt (peak), exposure, detector threshold, and readout mode revealed important considerations for system optimization. The model also demonstrated the important implications of false counts from both additive electronic noise and charge sharing and highlighted the system design and operational parameters that most affect detector performance in the presence of such factors: for example, increasing the detector threshold from 0 to 100 (arbitrary units of pulse height threshold roughly equivalent to 0.5 and 6 keV energy threshold, respectively), increased the f50 (spatial-frequency at which the MTF falls to a value of 0.50) by ∼30% with corresponding improvement in DQE. The range in exposure and additive noise for which PCDs yield intrinsically higher DQE was quantified, showing performance advantages under conditions of very low-dose, high additive noise, and high fidelity rejection of coincident photons. The model for PCD signal and noise performance agreed with measurements of detector signal, MTF, and NPS and provided a useful basis for understanding complex dependencies in PCD imaging performance and the potential advantages (and disadvantages) in comparison to EIDs as well as an important guide to task-based optimization in developing new PCD imaging systems.

For x-ray detectors, Compton interactions deposit photon energies along the paths of recoil electrons, which are not isotropic about the primary interaction sites. Light from each interacting x-ray is only generated near the path of a recoil electron. In this study, Compton scatter is modeled as an input-labeled cascade of the amplification and scattering processes to describe the transfer relationship of signal and noise in frequency space. The output of the model is the spatial distribution of secondary quanta generated by Compton recoil electrons. We determine the spatial dependence and statistical correlation of secondaries from the initial energy of the recoil electron and its range, resulting in the 'Compton' modulation transfer function (MTF) and noise power spectrum (NPS), respectively. Then the 'Compton' MTF and NPS are used to calculate the 'Compton' detective quantum efficiency (DQE). The probability density function of scattering angle of Compton recoil electron is developed using the Klein-Nishina coefficients. Results are applied to the description of a portal imaging system at 6 approximately MV where non-Compton interactions can be ignored. The MTF results are compared with a Monte Carlo calculation. This is the first model of how Compton interactions in the metal-plate/phosphor combination degrade image quality in terms of signal and noise. It is shown that Compton MTF depends on energy of x-ray photon in a complex way, and Compton scatter imposes a fundamental limitation on both the MTF and DQE of x-ray imaging system.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanel of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images. The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.

Purpose:Reducing patient dose while maintaining (or even improving) image quality is one of the foremost goals in CT imaging. To this end, we consider the feasibility of optimizing CT scan protocols in conjunction with the application of different beam‐hardening filtrations and assess this augmentation through noise‐power spectrum (NPS) and detector quantum efficiency (DQE) analysis.Methods:American College of Radiology (ACR) and Catphan phantoms (The Phantom Laboratory) were scanned with a 64 slice CT scanner when additional filtration of thickness and composition (e.g., copper, nickel, tantalum, titanium, and tungsten) had been applied. A MATLAB‐based code was employed to calculate the image of noise NPS. The Catphan Image Owl software suite was then used to compute the modulated transfer function (MTF) responses of the scanner. The DQE for each additional filter, including the inherent filtration, was then computed from these values. Finally, CT dose index (CTDIvol) values were obtained for each applied filtration through the use of a 100 mm pencil ionization chamber and CT dose phantom.Results:NPS, MTF, and DQE values were computed for each applied filtration and compared to the reference case of inherent beam‐hardening filtration only. Results showed that the NPS values were reduced between 5 and 12% compared to inherent filtration case. Additionally, CTDIvol values were reduced between 15 and 27% depending on the composition of filtration applied. However, no noticeable changes in image contrast‐to‐noise ratios were noted.Conclusion:The reduction in the quanta noise section of the NPS profile found in this phantom‐based study is encouraging. The reduction in both noise and dose through the application of beam‐hardening filters is reflected in our phantom image quality. However, further investigation is needed to ascertain the applicability of this approach to reducing patient dose while maintaining diagnostically acceptable image qualities in a clinical setting.

Cardiac x-ray detectors are used to acquire moving images in real-time for angiography and interventional procedures. Detective quantum efficiency (DQE) is not generally measured on these dynamic detectors; the required "for processing" image data and control of x-ray settings have not been accessible. By 2016, USA hospital physicists will have the ability to measure DQE and will likely utilize the International Electrotechnical Commission (IEC) standard for measuring DQE of dynamic x-ray imaging devices. The current IEC standard requires an image of a tilted tungsten edge test object to obtain modulation transfer function (MTF) for DQE calculation. It specifies the range of edge angles to use; however, it does not specify a preferred method to determine this angle for image analysis. The study aimed to answer the question "will my choice in method impact my results?" Four different established edge angle determination methods were compared to investigate the impact on DQE. Following the IEC standard, edge and flat field images were acquired on a cardiac flat-panel detector to calculate MTF and noise power spectrum, respectively, to determine DQE. Accuracy of the methods in determining the correct angle was ascertained using a simulated edge image with known angulations. Precision of the methods was ascertained using variability of MTF and DQE, calculated via bootstrapping. Three methods provided near equal angles and the same MTF while the fourth, with an angular difference of 6%, had a MTF lower by 3% at 1.5 mm(-1) spatial frequency and 8% at 2.5 mm(-1); corresponding DQE differences were 6% at 1.5 mm(-1) and 17% at 2.5 mm(-1); differences were greater than standard deviations in the measurements. DQE measurements may vary by a significant amount, depending on the method used to determine the edge angle when following the IEC standard methodology for a cardiac x-ray detector. The most accurate and precise methods are recommended for absolute assessments and reproducible measurements, respectively.

Medical images are acquired for the purpose of gathering information regarding the disease state of a patient. The quality of the image should be a measure of how a specified task may be performed given the resulting image. Image quality is task dependent; one imaging system may provide images that allow better task performance than another system's for one task, but worse for another task. Determining the quality of an imaging system involves specifying the task of interest, the range of objects that will be imaged, and the observer (human or machine reader) who will perform the task. In radiography it has become common to use Fourier measures to describe image quality through a combination of Fourier‐based measures of system resolution and noise. The Line Spread Function, when Fourier transformed, yields the Modulation Transfer Function (MTF) as a measure of system resolution. Use of the MTF to describe a system's resolution is appropriate when the imaging system is shift‐invariant, that is, the line spread function is independent of position. Image noise is described in the Fourier domain by the Noise Power Spectrum (NPS). We can use the NPS to describe the noise in an imaging system whenever the noise properties are stationary, meaning that the variance and correlations between fluctuations in different locations are not dependent on their absolute location. These Fourier measures of system resolution and noise are commonly combined to give an overall figure of merit known as the Detective Quantum Efficiency (DQE). The DQE describes the signal‐to‐noise transfer characteristics of an imaging system as long as those assumptions of shift‐invariance and noise stationarity are valid. In digital systems the image of an object is affected by the location of the object with respect to the pixel grid. In other words, the detector pixels cause the system to be shift‐variant. In this case the MTF does not describe the resolution properties completely. This is particularly the case for tomographic systems, where the point‐response function is quite position‐dependent. Moreover, in real imaging systems the noise properties will depend on position, most notably because real patients always have structure. So, the Fourier‐domain noise concept of Noise Power Spectrum does not capture all the properties of noise for real imaging systems and tasks. In this talk we will consider a general treatment of the imaging system as a mapping of information from the patient to the data, without the assumptions inherent in Fourier analysis. We will discuss approaches to the characterization of system resolution and noise in terms of position‐dependent parameters. Once such position‐dependent imaging properties of a system are determined, we can use them to calculate measures of image quality that summarize the usefulness of the images for the performance of various visual tasks.

In order to determine an objective measure of a system's image quality, we developed a simple, non-invasive measurement procedure to determine the detective quantum efficiency of digital radiographic systems, especially image intensifier-tv systems. Therefore we set up measurement procedures for the quantities intensity transfer function (ITF) (also called characteristic curve), modulation transfer function (MTF), noise power spectrum (NPS) and the low frequency drop (LFD). The quantities ITF, MTF, NPS and LFD are determined by the analysis of images of simple, standardized test objects (a slit, Al-filters of different thickness and a lead disk). The images are automatically evaluated by means of an Apple Macintosh workstation and the program NIH image with some special extensions. The resulting quantities MTF, NPS, LFD are combined to determine the noise equivalent quanta (NEQ) and the detective quantum efficiency (DQE). By means of this measurement procedure quantities, that describe the objective image quality like NEQ and DQE, can be determined in a simple way. Only a set of 45 images is needed for diagnosis of a system. This method provides a powerful analysis tool for image quality, that is applicable in the field and can be done from a remote location. It may be used in a clinical environment (e.g. in constancy testing).

The effect of incident x-ray beam quality on the measured detective quantum efficiency (DQE) of a computed radiography system was investigated. The incident x-ray beams used had peak tube potentials of 70, 95, and 120 kVp, were filtered with various thicknesses of a "patient equivalent phantom" (PEP), aluminum, and copper, and provided a consistent exposure to the storage phosphor. For each peak tube potential and filter combination, the one-dimensional modulation transfer function and noise power spectrum were measured and the square of the incident signal-to-noise ratio was estimated. The spatial frequency dependent DQE was calculated from these data. The DQE was integrated to provide an overall estimate of the efficiency and frequency response of the computed radiography system for the various x-ray beams. There was found to be a wide range of integral DQE (IDQE) values for the peak tube potential and filter combinations used. For example, the IDQE ranged from 3.0 to 0.9 mm(-2) using the peak tube potential and filter combinations 70 kVp with 5.1 cm PEP and 120 kVp with 30.3 cm PEP, respectively. Finally, peak tube potential and filter combinations 70 kVp with 10.2 cm PEP and 120 kVp with 20.2 cm PEP were chosen as standard x-ray beams that will be used at our facility to measure the DQE of digital radiographic imaging systems for evaluation and acceptance testing.

Alias reduction is analyzed with the concept of an equivalent presampling filter, and a mathematical approach is established to find the equivalent presampling filter corresponding to specific digital image processing algorithms. The effects of different sampling period T and sampling aperture tau on aliasing artifacts and on the resultant detective quantum efficiency (DQE) for a self-scanned, flat-panel, amorphous selenium detector are obtained. Different effective apertures can be obtained from the same detector by averaging signals over adjacent pixels. It is shown that adding outputs from M adjacent pixels is equivalent to introducing an equivalent presampling filter with special properties. Appropriate selection of the averaging parameters (M and weights) is shown to reduce the aliasing artifact in the resultant image. The effect of incomplete charge collection due to geometrical effects (fill factor) is examined. It is shown that a large fill factor is desirable for aliasing reduction. The relationship between a digital filter applied to the sampled signal and its equivalent presampling analog filter is also established. Analytical formulas for the sampled spectrum of white signal and for the sampled power spectrum of white noise are obtained for aperture functions with a spatially uniform response. These formulas take into accounts aliasing artifacts, signal correlation and aperture function response, and demonstrate the dependence of sampled spectra on T and tau. With these formulas the detective quantum efficiency DQE is derived. It is shown that the resultant DQE depends only on the fill factor and the size of readout electrode tau 0, but is completely independent of the degree or type of pixel averaging. That is, even though the pixel averaging method reduces aliasing it leaves DQE (omega) unchanged. When significant amplifier noise is present the DQE obtained with the pixel averaging method can be better than those obtained with an analog presampling filter. Finally, it is pointed out that the requirement of reducing aliasing artifacts conflicts with other requirements for a detector such as maximizing modulation transfer function (MTF). A careful and practical compromise has to be made by a detector designer in choosing the extent to which the aliasing artifacts are eliminated.

As a continuation of our digital radiographic sensor R&D, we have developed a digital gamma imaging system based upon the cadmium-telluride (CdTe) photoconductor for the applications of industrial gamma-imaging. The imaging system consists of a commercially-available CMOS pixel array of a 100 × 100 μm2 pixel size and a 5.4 × 151.0 mm2 active area, coupled with a 750-μm-thick CdTe photoconductor, and a collimated selenium (75Se) radioisotope of an about 2.3 × 1012 Bq activity and a physical size of 3.0 mm in diameter. In this study, we, for the first time, succeeded in obtaining useful gamma images of several test phantoms with the 75Se radioisotope from the imaging system and evaluated its imaging performance in terms of the line spread function (LSF), the modulation transfer function (MTF), the noise power spectrum (NPS), and the detective quantum efficiency (DQE). For comparison, we also tested its X-ray imaging performance with a microfocus X-ray tube of an about 5 μm focal spot size at an operation condition of 90 kVp and 100 μA. According to our test results, the designed imaging system seems to be promising for our ongoing application of nondestructive testings, provided that the effective source size of the 75Se radioisotope can be further limited.

The detective quantum efficiency (DQE) is a system parameter that can be used to accurately describe image noise transfer characteristics through many imaging systems. A simpler approach used by some investigators, particularly when evaluating new ideas and system designs, is to describe the system as a series of cascaded stages. Each stage may correspond to either an increase in the number of quanta (e.g., conversion from x-ray to optical quanta in a radiographic screen), or a loss (a detection or coupling probability). The number of secondary quanta at each stage per incident primary quantum is given by the product of all preceding gains, and can be displayed graphically for convenient interpretation. The stage with the fewest quanta is called the "quantum sink," limiting the pixel signal-to-noise ratio to less than the square root of the number of quanta per pixel. This conventional zero-spatial-frequency "quantum accounting diagram" (QAD), however, neglects the spatial spreading of secondary quanta and can seriously underestimate image noise. It is shown that this problem is avoided with the introduction of a spatial-frequency dependent QAD, expressed as the product of the gains and squared modulation-transfer functions (MTF) of each stage. A generalized expression is developed for the DQE of a cascaded imaging system that is dependent only on the gain, gain Poisson excess (related to the variance), and MTF, of each stage. A direct relationship is then shown to exist between the DQE and values in the QAD. The QAD of a hypothetical system consisting of a charge-coupled device camera and a scintillating screen is evaluated as an illustrative example. The conventional zero-frequency analysis suggests two quantum sinks occur with approximately equal importance: one in the number of x rays, and one in the number of optical quanta. The spatial-frequency dependent analysis, however, shows the optical quantum sink becomes severe and dominates at nonzero frequencies. The necessary increase in gain or optical numerical aperture required to prevent the optical quantum sink for spatial frequencies of interest is determined from the QAD analysis. The visual impact of this nonzero spatial-frequency quantum sink is shown in images generated using a Monte Carlo simulation of the cascading process.