KEYWORDS: Photons, Sensors, X-rays, X-ray detectors, Monte Carlo methods, Iodine, Scattering, Absorption, Mass attenuation coefficient, Signal detection
We report on the modeling, characterization, benchmarking, and optimization of an interventional cone beam CT system based on a dual layer X-ray detector by means of physics based simulations.
By Monte Carlo methods, we log the interaction and dose deposition (i.e. signal generation) of X-ray photons in the dual layer geometry, including scattering processes and fluorescence photon emission. From the spatial dose distribution inside the detection volume, we derive typical detector properties like X-ray spectral responses, detective quantum efficiencies 𝐷𝑄𝐸(0), and noise characteristics for particular detector layouts.
We apply these results in subsequent full system simulations to generate 3D imaging scans of dual layer spectral projections, for custom virtual phantoms containing inserts of e.g. blood sediment or iodine with different concentrations. These simulated images are used to calculate key performance indicators of the imaging system, like e.g. receiver operating characteristic based analysis of material separation capabilities.
Since aSi-based Flat Panel Detectors (FPD) were introduced in the early 2000’s with Trixell first generation of products considerable improvements have been brought incrementally to the products architectures and core technologies. Today, the 3rd generation of detectors achieve performances that seemed unreachable a decade ago … By combining advanced amorphous Silicon (aSi) sensor plate processes, high absorption and low ghosting indirect deposition CsI and the last generation of very fast and low noise readout ICs, detectors can run over 300 frame per second (fps) in binned mode and 60 fps in full resolution, while keeping sub 1000 e- electronic noise and maintaining Detective Quantum Efficiency (DQE) @5 nGy, @1 lp/mm, above 45%. This paper will show that a consistent product platform has been built around these optimized building blocks and that this platform is now ready for a complete portfolio allowing to serve the most demanding applications such as Radiography, ultra-low dose fluoroscopy, and even CT-like 3D imaging.
Dynamic X-ray imagers require large surface, fast and highly sensitive X-ray absorbers and dedicated readout
electronics. Monocrystalline photoconductors offer the sensitivity, speed, and MTF performances. Polycristalline
photoconductors offer the large surface at a moderate cost. The challenge for them is to maintain the first performances
at a compatible level with the medical applications requirements. This work has been focused on polycristalline CdTe
grown by Close Space Sublimation (CSS) technique. This technique offers the possibility to grow large layers with a
high material evaporation yield. This paper presents the results obtained with an image demonstrator using 350μm thick
CdTe_css layers coupled to a CMOS readout circuit with Indium bumping. The present demonstrator has 200 x 200
pixels, with a pixel pitch of 75μm ×75μm. A total image surface of 15mm × 15mm has then been obtained. The ASIC works in an integration mode, i.e. each pixel accumulates the charges coming from the CdTe layer on a capacitor, converting them to a voltage. Single images as well as video sequences have been obtained. X-ray performance at 16 frames per second rate is measured. In particular a readout noise of 0.5 X ray, an MTF of 50% at 4 lp/mm and a DQE of 20% at 4lp/mm and 600 nGy are obtained. Although present demonstrator surface is moderate, it demonstrates that high performance can be expected from this assembly concept and its interest for medical applications.
KEYWORDS: Denoising, Signal attenuation, Image filtering, Dual energy imaging, Sensors, Switches, Signal to noise ratio, Interference (communication), Calibration, Bone
Dual-energy imaging increases the possibility of pulmonary nodule detection by reducing the bone structure
noise. Dual-shot techniques are limited by structural artefacts due to patient and natural movement during the
switch of voltage between energies. A new acquisition approach for dual-energy imaging was envisioned in order
to reduce this inter-exposure time. The idea is to keep the tube voltage constant, switch a filter in front of
the patient and thus modulate the outgoing x-ray spectrum. The drawback of this method is a poorer spectral
separation between low and high energy images leading to a higher sensitivity to noise. On the other hand, noise
in the reconstructed image is mainly controlled by high-energy image noise, allowing the use of noise suppression
algorithms without loosing high-frequency information present in the low-energy image.
The first part of this paper is a simulation study presenting system optimisation that includes noise reduction in
the HE image. Exposure times and filter thickness are chosen when optimising the signal difference to noise ratio
(SDNR) and dose. Results show better SDNR (9 %) for similar dose than state-of-art dual-shot switching voltage
technique. Thicker filters could lead to better results, but would demand more tube charge. In the second part is
presented experimental validation and implemented noise suppression algorithm. As radiographs of anatomical
phantoms are structured, anisotropic algorithm have been considered. Nodule and anthropomorphic phantoms
were used to measure detail suppression after image processing. Results are shown in terms of noise suppression
in the reconstructed image as well as in detail preservation.
Dual-energy imaging increases the possibility of pulmonary nodule detection by reducing the bone structure
noise. The major problem of the dual-energy acquisition process with digital flat-panel detectors is the interval
of time between low-energy (LE) exposure and high-energy (HE) exposure. Due to misregistration between LE
and HE images, motion artifacts pollute the subtracted image. This paper presents a new acquisition approach
for dual-energy imaging developed in order to reduce this inter-exposure time. The idea is to keep the tube
voltage constant and to just switch a filter in front of the imaged object and thus to modulate the outgoing x-ray
spectrum.
The first part of this study presents how to optimize system parameters for the new acquisition protocol:
source voltage, dynamic filtration before the patient, exposure time for LE and HE acquisition. The tube load
is kept constant to focus the optimization study on the dose and the exposure time. A noise quality factor
(NQF) and a spectral quality factor (SQF) are used as criteria for optimization. The new approach system is
then compared to the state-of-the-art system with voltage switching between low and high energy. A filtering
algorithm of dual energy acquisitions enabling a significant noise reduction is presented. Performance between its
combination with the new acquisition protocol and the reference one are compared. For a limited noise quality
factor, three times faster acquisition time is obtained using the new system. Noise reduction techniques improve
the image SNR by 61% in the new system and only 32% in the reference system, without taking into account
the impact of better registration on the dual-energy image quality.
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