We study flat detectors for X-ray imaging performance degradation. In cone beam C-arm-CT, memory effects have a
detrimental effect on image quality. Depending on the magnitude and history of irradiance differences, detector
sensitivity variations may persist for a long period of time (days) and are visible as rings upon 3D reconstruction. A new
method is proposed for reducing memory effects produced in CsI:Tl based Flat Detector X-ray imaging, which is based
upon trap-filling by UV-light. For experiments, a commercial detector has been modified such that UV back-lighting is
accomplished. A regular LED refresh light array for reducing photodiode temporal effects is interleaved with UV LED
sub-arrays of different wavelengths in the near UV range. The array irradiates the scintillator through translucent parts of
the detector substrate. In order to assess the efficacy of the method, ghost images are imprinted by well-defined
transitions between direct radiation and attenuated or shuttered radiation. As an advantage, the new method accomplishes
ghost-prevention, either by (1) continuous trap-filling at image-synchronous UV light pulsing, or (2) by applying a single
dose of UV light. As a result, ring artefacts in reconstructed
3D-images are reduced to low levels. An effective
wavelength has been found and an equilibrium UV dosage could be set for effective trap-filling. The overall sensitivity
of the detector increases at saturated trap-filling. It was found that with optimised detector settings, i.e. optimum
saturated trap-filling, the dependence on X-ray irradiation levels is low, so that the usage of the detector and its
performance is robust.
KEYWORDS: Interference (communication), X-ray imaging, X-rays, Quantization, Image quality, Image processing, Signal to noise ratio, Chest, Signal processing, Medical imaging
This work aims at defining an information-theoretic quality assessment technique for cardiovascular X-ray
images, using a full-reference scheme (relying on averaging a sequence to obtain a noiseless reference). With the
growth of advanced signal processing in medical imaging, such an approach will enable objective comparisons
of the quality of processed images. A concept for describing the quality of an image is to express it in terms
of its information capacity. Shannon has derived this capacity for noisy channel coding. However, for X-ray
images, the noise is signal-dependent and non-additive, so that Shannon's theorem is not directly applicable.
To overcome this complication, we exploit the fact that any invertible mapping on a signal does not change
its information content. We show that it is possible to transform the images in such a way that the Shannon
theorem can be applied. A general method for calculating such a transformation is used, given a known relation
between signal mean and noise standard deviation. After making the noise signal-independent, it is possible to
assess the information content of an image and to calculate an overall quality metric (e.g. information capacity)
which includes the effects of sharpness, contrast and noise. We have applied this method on phantom images
under different acquisition conditions and computed the information capacity for those images. We aim to show
that the results of this assessment are consistent with variations in noise, contrast and sharpness, introduced by
system settings and image processing.
KEYWORDS: 3D modeling, Modulation transfer functions, X-rays, X-ray imaging, 3D image processing, 3D image reconstruction, Image quality, 3D metrology, Imaging systems, Sensors
Nowadays, 2D X-ray systems are used more and more for 3-dimensional rotational X-ray imaging (3D-RX) or volume imaging, such as 3D rotational angiography. However, it is not evident that the application of settings for optimal 2D images also guarantee optimal conditions for 3D-RX reconstruction results. In particular the search for a good compromise between patient dose and IQ may lead to different results in case of 3D imaging. For this purpose we developed an additional 3D-RX module for our full-scale image quality & patient dose (IQ&PD) simulation model, with specific calculations of patient dose under rotational conditions, and contrast, sharpness and noise of 3D images.
The complete X-ray system from X-ray tube up to and including the display device is modelled in separate blocks for each distinguishable component or process. The model acts as a tool for X-ray system design, image quality optimisation and patient dose reduction. The model supports the decomposition of system level requirements, and takes inherently care of the prerequisite mutual coherence between component requirements. The short calculation times enable comprehensive multi-parameter optimisation studies.
The 3D-RX IQ&PD performance is validated by comparing calculation results with actual measurements performed on volume images acquired with a state-of-the-art 3D-RX system. The measurements include RXDI dose index, signal and contrast based on Hounsfield units (H and ΔH), modulation transfer function (MTF), noise variance (σ2) and contrast-to-noise ratio (CNR).
Further we developed a new 3D contrast-delta (3D-CΔ) phantom with details of varying size and contrast medium material and concentration. Simulation and measurement results show a significant correlation.
In reference 1 we have presented the principle of an X-ray detector based upon a screen coupled to an array of multiple CCD sensors. In reference 2 we focus on the characterization of the image quality: resolution (MTF) and noise behavior in the overlap area. Simple (and cheap) low F# lenses likely show distortion which means that not all imaged pixels have the same magnification. This may affect resolution. Lenses with (some) barrel distortion have the benefit of less vignetting. The correction of distortion in combination with a rotation adjustment requires interpolation. Interpolation affects the noise properties so care must be taken in order to avoid that the noise characterization of the reconstructed image mosaic i.e. the noise texture becomes spatially non uniform. We present an analysis of the influence of lens distortion and interpolation in cases of small rotation correction on the image mosaic. The image processing appears not to diminish the image quality provided the processing parameters are set correctly. The calibration of the imaging mosaic geometry is crucial. We therefore present a robust extraction algorithm. In this paper our main interest is on MTF and quantum noise properties. The lab prototype hardware is designed such (cubic spline interpolation) that also the lens distortion can be compensated. For this purpose ASICs are designed by the company AEMICS. This enables relative cheap optical components with low F# and a short building length. We have obtained and will present radiographic exposures of static phantoms.
We have presented the principle of an x-ray detector based upon a screen coupled to an array of multiple CCD sensors. We now focus on the characterization of the image quality: resolution (MTF) and noise behavior in the overlap area. Simple low F lenses likely show distortion which means that not all imaged pixels have the same magnification. This may affect resolution. In the overlap area the image is reconstructed by interpolation between two sensors. Interpolation affects the noise properties so care must be taken in order to avoid that the noise characterization of the reconstructed image mosaic becomes spatially non uniform.We present an analysis of the influence of lens distortion and interpolation in the overlap area on the image mosaic. The image processing appears not to diminish the image quality provided the processing parameters are set correctly. We therefore present a robust extraction algorithm. In order to evaluate in real-time the image quality of the proposed detector system, we are building a 2 by 2 lens-CCD sensor system as a lab prototype. The main interest is on MTF and quantum noise properties. The hardware is designed such that also the lens distortion can be compensated. This enables relative cheap optical components with low F and a short building length. We have obtained and will present radiographic exposures of static phantoms.
In this contribution we propose an alternative x-ray detector based upon multiple screen-CCD sensor combinations. The impinging x-ray quanta are detected by a scintillator screen (e.g. CsI) and converted to light photons (typ. 1200 photons per absorbed x-ray quantum). We propose a number of lens-CCD sensors for standard video performance to detect the light photons coming out of an x-ray intensifying screen. Due to the smaller demagnification the coupling efficiency is better even with moderate quality (F number) lenses. We thus obtain a matrix of subimages, the system is constructed such that the subimages partially overlap. With digital image processing we construct from the subimages a single high quality image. Special hardware (incl. ASICS) has been developed for imaging at video rates, enabling (almost) fluoroscopy with this new detector. We show a viable digital x-ray imaging detector concept by means of our 2 by 2 CCD camera prototype and real-time processing engine. The image quality, MTF and noise properties are satisfactory and well in the diagnostic application range.
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