Ulrich Neitzel

Grids or air gaps for scatter reduction in digital radiography: A model calculation

The relative advantages of grids and air gaps for scatter reduction in a digital radiography system were investigated using a theoretical model. In this model the properties of the scatter reduction device are described by primary transmission and selectivity. The signal-to-noise (SNR) improvement factor for fixed exposure to the patient was used as a performance indicator. The results show that the SNR improvement depends strongly on the local scatter fraction; for all practical configurations, however, it stays below a factor of 2. For high scatter fractions, an air gap of 20 cm has about the same effect on SNR improvement as a highly selective grid; for low and medium scatter conditions the air gap performs better than any grid. Additive system noise reduces the SNR improvement factor compared to the case with quantum noise only, the reduction being more pronounced for the grids than for the air gap. The results suggest that the use of an air gap instead of a grid is advantageous in digital radiography systems.

X‐ray diffraction computed tomography

Coherent scattering of x-ray photons leads to the phenomenon of x-ray diffraction, which is widely used for determining atomic structure in materials science. A technique [x-ray diffraction computed tomography (CT)] is described, analogous to conventional CT, in which the x-ray diffraction properties of a stack of two-dimensional object sections may be imaged. The technique has been investigated using a first generation (single pencil beam) CT scanner to measure small angle coherent scatter, in addition to the customary transmitted radiation. Diffraction data from a standard CT performance phantom obtained with this new technique and with an x-ray diffractometer are compared. The agreement is satisfactory bearing in mind the poor momentum resolution of our apparatus. The dose and sensitivity of x-ray diffraction CT are compared with those of conventional transmission CT. Diffraction patterns of some biological tissues and plastics presented in a companion paper indicate the potential of x-ray diffraction CT for tissue discrimination and material characterization. Finally, possibilities for refinement of the technique by improving the momentum resolution are discussed.

Image quality of a digital chest radiography system based on a selenium detector

A digital chest radiography system has been developed, with a detector based on the photoelectric properties of amorphous selenium. The selenium layer is deposited on a cylindrical aluminium drum, large enough to cover the full field of view for chest imaging. The electrostatic charge image which is formed on the selenium surface after x-ray exposure is read out by electrometer probes using fast drum rotation. For a physical evaluation of the attainable image quality, the characteristic curve, the modulation transfer function, and the noise spectra were measured. From these measurements, the signal-to-noise properties of the detector in terms of detective quantum efficiency (DQE) and noise equivalent quanta (NEQ) were derived. The results show that the selenium-based detector has a wide dynamic range and a significantly better DQE than screen-film and storage phosphor systems for spatial frequencies below the Nyquist limit (2.7 lp/mm). As a consequence, the detectability of small, low-contrast details is considerably improved.

X-Ray diffraction measurements of some plastic materials and body tissues

X-ray diffraction allows the investigation of the atomic or molecular structure of materials. The combination of diffractometry with computerized tomography enables spatially resolved imaging of the diffraction properties of extended objects as described in more detail in a companion article [Harding et al., Med. Phys. 14, 515 (1987)]. We present measured diffraction patterns of some plastics and several biological materials, which allow further optimization of our method and the selection of suitable application areas.

Accuracy of a simple method for deriving the presampled modulation transfer function of a digital radiographic system from an edge image

Several methods for accurately deriving the presampled modulation transfer function (MTF) of a pixelated detector from the image of a slightly slanted edge have been described in the literature. In this paper we report on a simple variant of the edge method that produces sufficiently accurate MTF values for frequencies up to the Nyquist frequency limit of the detector with little effort in edge alignment and computation. The oversampled ESF is constructed in a very simple manner by rearranging the pixel data of N consecutive lines corresponding to a lateral shift of the edge by one pixel. A regular subsampling pitch is assumed for the oversampled ESF, which is given by the original pixel sampling distance divided by the integer number N. This allows the original data to be used for further computational analysis (differentiation and Fourier transform) without data preprocessing. Since the number of lines leading to an edge shift by one pixel generally is a fractional number rather than an integer, a systematic error may be introduced into the presampled MTF. Simulations and theoretical investigations show that this error is proportional to 1/N and increases with spatial frequency. For all frequencies up to the Nyquist limit, the relative error delta MTF/MTF is smaller than 1/(2N). It can thus be kept below a given threshold by suitably selecting N, which furnishes a certain maximum edge angle. The method is especially useful for applications where the presampled MTF is needed only for frequencies up to the Nyquist frequency limit, such as the determination of the detective quantum efficiency (DQE).

Digital chest radiography: an update on modern technology, dose containment and control of image quality

The introduction of digital radiography not only has revolutionized communication between radiologists and clinicians, but also has improved image quality and allowed for further reduction of patient exposure. However, digital radiography also poses risks, such as unnoticed increases in patient dose and suboptimum image processing that may lead to suppression of diagnostic information. Advanced processing techniques, such as temporal subtraction, dual-energy subtraction and computer-aided detection (CAD) will play an increasing role in the future and are all targeted to decrease the influence of distracting anatomic background structures and to ease the detection of focal and subtle lesions. This review summarizes the most recent technical developments with regard to new detector techniques, options for dose reduction and optimized image processing. It explains the meaning of the exposure indicator or the dose reference level as tools for the radiologist to control the dose. It also provides an overview over the multitude of studies conducted in recent years to evaluate the options of these new developments to realize the principle of ALARA. The focus of the review is hereby on adult applications, the relationship between dose and image quality and the differences between the various detector systems.

Determination of the detective quantum efficiency of a digital x-ray detector: Comparison of three evaluations using a common image data set

The detective quantum efficiency (DQE) of an x-ray digital imaging detector was determined independently by the three participants of this study, using the same data set consisting of edge and flat field images. The aim was to assess the possible variation in DQE originating from established, but slightly different, data processing methods used by different groups. For the case evaluated in this study differences in DQE of up to +/-15% compared to the mean were found. The differences could be traced back mainly to differences in the modulation transfer function (MTF) and noise power spectrum (NPS) determination. Of special importance is the inclusion of a possible low-frequency drop in MTF and the proper handling of signal offsets for the determination of the NPS. When accounting for these factors the deviation between the evaluations reduced to approximately +/-5%. It is expected that the recently published standard on DQE determination will further reduce variations in the data evaluation and thus in the results of DQE measurements.

Simple method for modulation transfer function determination of digital imaging detectors from edge images

A simple variant of the edge method to determine the presampled modulation transfer function (MTF) of digital imaging detectors has been developed that produces sufficiently accurate MTF values for frequencies up to the Nyquist frequency limit of the detector with only a small amount of effort for alignment and computing. An oversampled edge spread function (ESF) is generated from the image of a slanted edge by rearranging the pixel data of N consecutive lines that correspond to a lateral shift of the edge of one pixel. The original data are used for the computational analysis without further data preprocessing. Since the number of lines leading to an edge shift of one pixel is generally a fractional number rather than an integer, a systematic error may be introduced in the MTF obtained. Simulations and theoretical investigations show that for all frequencies up to the Nyquist limit the relative error ΔMTF/MTF is below 1/(2N) and can thus be kept below a given threshold by a suitable choice of N. The method is especially useful for applications where the MTF is needed for frequencies up to the Nyquist frequency limit, like the determination of the detective quantum efficiency (DQE).

Determination of the modulation transfer function using the edge method: influence of scattered radiation.

The edge method for measuring the modulation transfer function (MTF) has recently gained popularity due to its simplicity and appropriateness particularly for digital imaging systems. Often edge test devices made of rather thin metal sheets are used, which are semitransparent to x rays and may generate scattered radiation. The effect of this scattered radiation on the determined MTF was investigated both theoretically (assuming an ideal detector) and experimentally using a CsI-based digital detector. It was found that the MTF increases due to the scattered radiation for all spatial frequencies larger than 0 mm(-1). The theoretical model developed in this study predicts that the maximum error compared to the true detector MTF is given by S/A, where A is the attenuated fraction and S is the scattered fraction reaching the detector, relative to the incident radiation. Theoretical and experimental results are in good agreement for radiation qualities corresponding to general radiography (RQA3, RQA5, and RQA7), whereas for chest beam quality (RQA9) the experimentally observed MTF error is larger than predicted by the simple model, possibly because the energy response of the CsI-based detector differs from that of an ideal one. The theoretical MTF error reaches a value of 18% for a 0.25 mm thick lead edge of RQA9. Since the MTF enters squared into the determination of the detective quantum efficiency (DQE), an error of at least 36% in DQE may result when using this edge test device. In conclusion, the use of fully absorbing edge material is advised for MTF determination with the edge method.

Principles of image processing in digital chest radiography.

Image processing has a major impact on image quality and diagnostic performance of digital chest radiographs. Goals of processing are to reduce the dynamic range of the image data to capture the full range of attenuation differences between lungs and mediastinum, to improve the modulation transfer function to optimize spatial resolution, to enhance structural contrast, and to suppress image noise. Image processing comprises look-up table operations and spatial filtering. Look-up table operations allow for automated signal normalization and arbitrary choice of image gradation. The most simple and still widely applied spatial filtering algorithms are based on unsharp masking. Various modifications were introduced for dynamic range reduction and MTF restoration. More elaborate and more effective are multi-scale frequency processing algorithms. They are based on the subdivision of an image in multiple frequency bands according to its structural composition. This allows for a wide range of image manipulations including a size-independent enhancement of low-contrast structures. Principles of the various algorithms will be explained and their impact on image appearance will be illustrated by clinical examples. Optimum and sub-optimum parameter settings are discussed and pitfalls will be explained.