Measurements of the noise power spectrum for digital x-ray imaging devices

Objective.The noise characteristics of digital x-ray imaging devices are determined by contributions such as photon noise, electronic noise, and fixed pattern noise, and can be evaluated from measuring the noise power spectrum (NPS), which is the power spectral density of the noise. Hence, accurately measuring NPS is important in developing detectors for acquiring low-noise digital x-ray images. To make accurate measurements, it is necessary to understand NPS, identify problems that may arise, and know how to process the obtained x-ray images.Approach.The primitive concept of NPS is first introduced with a periodogram-based estimate and its bias and variance are discussed. In measuring NPS based on the IEC62220 standards, various issues, such as the fixed pattern noise, high-precision estimates, and lag corrections, are summarized with simulation examples.Main results.High-precision estimates can be provided for an appropriate number of samples extracted from x-ray images while compromising spectral resolution. Depending on medical imaging systems, by eliminating the influence of fixed pattern noise, NPS, which represents only photon and electronic noise, can be efficiently measured. For NPS measurements in dynamic detectors, an appropriate lag correction technique can be selected depending on the emitted x-rays and image acquisition process.Significance.Various issues in measuring NPS are reviewed and summarized for accurately evaluating the noise performance of digital x-ray imaging devices.

A novel grid regression demodulation method for radiographic grid artifact correction

PURPOSE

In x-ray radiography, the commonly used antiscatter grid for enhancing image quality causes artifacts in the form of periodic noises, such as shadows, cutoff, and Moiré fringes. Software degridding is traditionally performed via linear or homomorphic filtering in the spectral domain. These methods inevitably result in image blurring, information loss, and distortion, thus hindering detection and assessment of diseases. We seek effective and practical solutions for grid artifact correction based on spatial-domain analysis toward high-quality imaging.

METHODS

By analyzing the physical process of grid artifact formation, we track down the root of the problem associated with spectral filtering. We propose the grid regression demodulation (GRD). The degridding cost is forged as a functional of the latent x-ray photon image and parametric grid model characterizing grid transmission property. Regularization on the grid spectra is incorporated. We devise optimization algorithms for artifact correction and grid pattern estimation. GRD decouples the partially overlapped spectra of the grid and anatomy, and removes the artifacts independently, thus restoring the underlying clinically relevant data.

RESULTS

Method efficacy is demonstrated using simulated and real data. GRD effectively preserves image edges, textures, and patterns while removing grid artifacts. For the known ground truth setting, GRD gives a near-perfect correction. For real data, GRD is capable of correcting not only the primary grid artifacts, but also the higher grid harmonic artifacts while keeping image content unaltered, which is unachievable by the other methods. Our method has low residual errors and exhibits a successful demodulation effect without introducing additional artifacts, while ringing or cilia artifacts are present in the others.

CONCLUSIONS

The proposed method outperforms the prevalent transform techniques for correcting grid artifacts in digital radiography. It is self-sustained and self-adaptive to a range of targets and beam quality. Our approach is advantageous in restoring the latent image while suppressing grid noises. It retrieves the true scale factor of the degridded data, which is unattainable via any spectral filtering techniques. This work unlocks a promising venue to improve and upgrade low-dose medical radiographic imaging technology.

Air gap technique is recommended in axiolateral hip radiographs

Purpose

To investigate the replacement of conventional grid by air gap in axiolateral hip radiographs. The optimal air gap distance was studied with respect to radiation dose and image quality using phantom images, as well as 26 patient axiolateral hip radiographs.

Methods

The CDRAD phantom, along with polymethylmethacrylate slabs with thicknesses of 10.0, 14.6, and 20.0 cm was employed. The inverse image quality index and dose area product (DAP), as well as their combination, so called figure‐of‐merit (FOM) parameter, were evaluated for these images, with air gaps from 20 to 50 cm in increments of 10 cm. Images were compared to those acquired using a conventional grid utilized in hip radiography. Radiation dose was measured and kept constant at the surface of the detector by using a reference dosimeter. Verbal consent was asked from 26 patients to participate to the study. Air gap distances from 20 to 50 cm and tube current‐time products from 8 to 50 mAs were employed. Exposure index, DAP, as well as patient height and weight were recorded. Two radiologists evaluated the image quality of 26 hip axiolateral projection images on a 3‐point nondiagnostic — good/sufficiently good — too good scale. Source‐to‐image distance of 200 cm and peak tube voltage of 90 kVp were used in both studies.

Results and conclusion

Based on the phantom study, it is possible to reduce radiation dose by replacing conventional grid with air gap without compromising image quality. The optimal air gap distance appears to be 30 cm, based on the FOM analysis. Patient study corroborates this observation, as sufficiently good image quality was found in 24 of 26 patient radiographs, with 7 of 26 images obtained with 30 cm air gap. Thus, air gap method, with an air gap distance of 30 cm, is recommended in axiolateral hip radiography.

A new software scheme for scatter correction based on a simple radiographic scattering model

In common radiography, image contrast is often limited due mainly to scattered x-rays and noise, decreasing the quantitative usefulness of x-ray images. Several scatter reduction methods based on software correction schemes have been extensively investigated in an attempt to overcome these difficulties, most of which are based on measurement, mathematical-physical modeling, or a combination of both. However, those methods require special equipment, system geometry, and extra manual work to measure scatter characteristics. In this study, we investigated a new software scheme for scatter correction based on a simple radiographic scattering model where the intensity of the scattered x-rays was directly estimated from a single x-ray image using a weighted l¹-norm contextual regularization framework. We implemented the proposed algorithm and performed a systematic simulation and experiment to demonstrate its viability. We also conducted some clinical image studies using patient's image data of breast and L-spine to verify the clinical effectiveness of the proposed scheme. Our results indicate that the degradation of image characteristics by scattered x-rays and noise was effectively recovered by using the proposed software scheme, thus improving radiographic visibility considerably. Graphical abstract The schematic illustrations of scatter suppression methods by using a an antiscatter grid and b a scatter estimation algorithm.

Patch Based Grid Artifact Suppressing in Digital Mammography

The mammography is the first choice of breast cancer screening, which has proven to be the most effective screening method. An antiscatter grid is usually employed to enhance the contrast of image by absorbing unexpected scattered signals. However, the grid pattern casts shadows and grid artifacts, which severely degrade the image quality. To solve the problem, we propose the patch based frequency signal filtering for fast grid artifacts suppressing. As opposed to whole image processing synchronously, the proposed method divides image into a number of blocks for tuning filter simultaneously, which reduces the frequency interference among image blocks and saves computation time by multithread processing. Moreover, for mitigating grid artifacts more precisely, characteristic peak detection is employed in each block automatically, which can accurately identify the location of the antiscatter grid and its motion pattern. Qualitative and quantitative studies were performed on simulation and real machine data to validate the proposed method. The results show great potential for fast suppressing grid artifacts and generating high quality of digital mammography.

Design and evaluation of a grid reciprocation scheme for use in digital breast tomosynthesis

This work describes a methodology for efficient removal of scatter radiation during digital breast tomosynthesis (DBT). The goal of this approach is to enable grid image obscuration without a large increase in radiation dose by minimizing misalignment of the grid focal point (GFP) and x-ray focal spot (XFS) during grid reciprocation. Hardware for the motion scheme was built and tested on the dual modality breast tomosynthesis (DMT) scanner, which combines DBT and molecular breast tomosynthesis (MBT) on a single gantry. The DMT scanner uses fully isocentric rotation of tube and x-ray detector for maintaining a fixed tube-detector alignment during DBT imaging. A cellular focused copper prototype grid with 80 cm focal length, 3.85 mm height, 0.1 mm thick lamellae, and 1.1 mm hole pitch was tested. Primary transmission of the grid at 28 kV tube voltage was on average 74% with the grid stationary and aligned for maximum transmission. It fell to 72% during grid reciprocation by the proposed method. Residual grid line artifacts (GLAs) in projection views and reconstructed DBT images are characterized and methods for reducing the visibility of GLAs in the reconstructed volume through projection image flat-field correction and spatial frequency-based filtering of the DBT slices are described and evaluated. The software correction methods reduce the visibility of these artifacts in the reconstructed volume, making them imperceptible both in the reconstructed DBT images and their Fourier transforms.

Limitations of anti-scatter grids when used with high resolution image detectors

Anti-scatter grids are used in fluoroscopic systems to improve image quality by absorbing scattered radiation. A stationary Smit Rontgen X-ray grid (line density: 70 lines/cm, grid ratio: 13:1) was used with a flat panel detector (FPD) of pixel size 194 micron and a high-resolution CMOS detector, the Dexela 1207 with pixel size of 75 microns. To investigate the effectiveness of the grid, a simulated artery block was placed in a modified uniform frontal head phantom and imaged with both the FPD and the Dexela for an approximately 15 × 15 cm field of view (FOV). The contrast improved for both detectors with the grid. The contrast-to-noise ratio (CNR) does not increase as much in the case of the Dexela as it improves in the case of the FPD. Since the total noise in a single frame increases substantially for the Dexela compared to the FPD when the grid is used, the CNR is degraded. The increase in the quantum noise per frame would be similar for both detectors when the grid is used due to the attenuation of radiation, but the fixed pattern noise caused by the grid was substantially higher for the Dexela compared to the FPD and hence caused a severe reduction of CNR. Without further corrective methods this grid should not be used with high-resolution fluoroscopic detectors because the CNR does not improve significantly and the visibility of low contrast details may be reduced. Either an anti-scatter grid of different design or an additional image processing step when using a similar grid would be required to deal with the problem of scatter for high resolution detectors and the structured noise of the grid pattern.