Indirect photon-counting x-ray imaging using CMOS Photon Detector (CPD)

Technological innovations over the past several decades have led to pixelated photon-counting x-ray detectors suitable for medical imaging applications. One component of this research effort is the development of mathematical models of detector performance. Such models provide physical insight and understanding of relationships between the basic physics of photon-counting x-ray detectors and image quality. Models also enable identifying upper limits of detector performance, establishing performance benchmarks, and optimizing detector design. Over the past several decades, the image science community developed a Fourier-based approach to the objective assessment of detector performance. Within this framework, image spatial resolution and image noise are quantified in terms of the modulation transfer function and noise power spectrum, respectively. These metrics are combined in the detective quantum efficiency, which provides an objective measure of the signal-to-noise performance of an x-ray imaging system as a function of spatial frequency. In this chapter, we summarize recent efforts to develop a framework for modelling and understanding of Fourier-based metrics of the performance of photon-counting x-ray detectors. We present a brief introduction to Fourier-based metrics of image quality, present a generic framework for modelling of Fourier-based metrics for photon-counting systems, and then present a simple model of a photon-counting detector that enables understanding relationships between detector design parameters, spatial resolution, and image noise. The development of models of the performance of photon-counting x-ray imaging systems is an ongoing effort and future research is expected to transcend the material presented in this chapter.

The photon counting image collected under 10− 4 lux environment has a degraded image quality due to background noises and other problems. Bayesian estimation is a classical approach for photon counting image restoration and regularization has also been widely used in image processing. However, the regularization method is not suitable for photon counting images with extremely lack of information, and the recovery effect of Bayesian estimation in images mixed with unknown noise is not ideal. The main contribution of this paper is that on the basis of Bayesian estimation, the regularization method is introduced to solve the problem of restoring photon counting images mixed with unknown noise under 10− 4 lux environment. The original part is that the gamma distribution of the expected value of photon counting is used as its prior condition, and the error function is expressed as the form of the norm to establish the objective function. Through an approximate iterative solution, the optimal estimation of the photon counting expectation is carried out to achieve the optimal restoration of the photon counting image. Experiments demonstrate that the background noise is effectively removed and the image quality is improved after restoring photon counting images. Also, the final result of the proposed method is superior to other comparative methods in multiple evaluation indexes and achieved better effects.

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.

We developed and evaluated an x-ray photon-counting imaging system using an energy-resolving cadmium zinc telluride (CZT) detector coupled with application specific integrated circuit (ASIC) readouts. This x-ray imaging system can be used to identify different materials inside the object. The CZT detector has a large active area (5×5 array of 25 CZT modules, each with 16×16 pixels, cover a total area of 200 mm × 200 mm), high stopping efficiency for x-ray photons (~ 100 % at 60 keV and 5 mm thickness). We explored the performance of this system by applying different energy windows around the absorption edges of target materials, silver and indium, in order to distinguish one material from another. The photon-counting CZT-based x-ray imaging system was able to distinguish between the materials, demonstrating its capability as a radiation-spectroscopic decomposition system.

Today, CCD and CMOS image sensors have found many applications in general public domains. However their use for scientific and space applications requires high electro optical performances and strong abilities to predict them prior to the image sensors design and conception. Sensitivity and image quality are two important electro-optical characteristics for an image sensor. The Quantum Efficiency (QE) and the Modulation Transfer Function (MTF) are respectively the common metrics used to quantify them. Because of an important number of parameters influencing the MTF and the QE, their analytical calculation is not an easy task. This paper describes an analytical model of MTF and QE of CCD and CMOS image sensors. The model has been developed in order to take into account a maximum number of parameters: pixel size, photosensitive area size and shape, EPI-layer and substrate doping concentration, junction depth. The effect of top layer oxide stacks on the resulting optical transmission coefficient and so on QE can also be taken into account. The study is established in the case of CMOS photodiode pixels and buried channel CCD pixels. The MTF and QE modeling results are compared with experimental results. MTF and QE measurements are realized on different pixels types having different photosensitive area shapes and using different technologies. A part of these measurements are performed on a frontside-illuminated CMOS sensor and on a thinned backside-illuminated CMOS image sensor, both of them are manufactured using CMOS technology dedicated to image sensors. The other part of MTF and QE measurements are performed on thinned backside-illuminated N-buried channel CCD sensor. Finally the MTF and QE models are used to make performance predictions, and the effects of various parameters on the MTF and the QE are discussed.

We study the influence of the locations of energy thresholds on the basis image noise in spectral X-ray imaging using photon counting devices. Our simulations assume photon counting detectors equipped with up to four discriminator units allowing the binning of photons into up to four distinct energy windows. We use the binned counting data in order to compute the Cramer-Rao lower bound (CRB) for the basis image noise in a photo-effect -Compton-effect decomposition of the attenuation. By studying the variations of the CRB with respect to the threshold energies, we obtain optimized arrangements for each number of energy thresholds and for different values of external copper filtration. We compare the basis image noise for the optimal arrangement with the noise corresponding to an equidistant threshold arrangement and with the results of a tube dual-energy acquisition. Our simulations were performed on two different X-ray paths corresponding to two perpendicular directions through the human thorax. Our results show that in many cases the basis image noise can be strongly reduced by optimizing the locations of the threshold energies.

The pixel array of BSI CMOS image sensor is a kind of photoelectric device to obtain 2D image information. The image quality was evaluated by the modulation transfer function (MTF) of BSI CMOS image sensor pixel at Nyquist frequency. With the decreasing pixel size of BSI CMOS image sensor and the increasing spatial resolution, it is more and more difficult to improve the MTF at Nyquist frequency. According to the theoretical analysis, MTF is composed of aperture MTF and diffusion MTF, the comprehensive MTF function is usually obtained by the multiplication relationship between the two MTFs in the frequency domain. Aperture MTF and diffusion MTF have different influence factors and calculation functions, but they are related to the size of the opening. The opening here represents the sensitivity aperture and photo-sense region respectively. The smaller the opening of the detector pixel, the larger MTF will be. In this paper, the theoretical mechanism of MTF function is analyzed in detail, and the calculation results of MTF of BSI CMOS image sensor pixel under 8 typical optical wavelengths in 300nm-1000nm spectral band are listed.

In this paper, the meaning and appropriateness of complementary metal-oxide-semiconductor image sensor (CIS) modulation transfer function (MTF) is reconsidered. Two-dimensional (2-D) submicrometer spot scanning results are presented for industrial CIS, 2-D-MTF, characterizing CIS performance and resolution abilities is extracted and compared with the ideal one-dimensional (1-D) MTF profile estimation calculated for all spatial frequencies. "Inter" and "intra" pixel MTFs emphasizing pixel structure dependencies are defined. The domain of applicability of traditional 1-D sensor characterization methods is shown to be ambiguous and insufficient for modern anisotropic CIS designs, resembling the inability to account for the sensor internal structural effects. Furthermore, it was shown that 2-D characterization provides reliable information and enables better understanding and the most accurate description of device performance. In addition, the advantages (over the commonly referred 1-D-MTF) and necessities of 2-D-MTF are verified experimentally and clearly demonstrated in this paper

To compare imaging performance of a cadmium telluride (CdTe) based photon counting detector (PCD) with a CMOS based energy integrating detector (EID) for potential phase sensitive imaging of breast cancer. A high energy inline phase sensitive imaging prototype consisting of a microfocus X-ray source with geometric magnification of 2 was employed. The pixel pitch of the PCD was 55μm, while 50μm for EID. The spatial resolution was quantitatively and qualitatively assessed through modulation transfer function (MTF) and bar pattern images. The edge enhancement visibility was assessed by measuring edge enhancement index (EEI) using the acrylic edge acquired images. A contrast detail (CD) phantom was utilized to compare detectability of simulated tumors, while an American College of Radiology (ACR) accredited phantom for mammography was used to compare detection of simulated calcification clusters. A custom-built phantom was employed to compare detection of fibrous structures. The PCD images were acquired at equal, and 30% less mean glandular dose (MGD) levels as of EID images. Observer studies along with contrast to noise ratio (CNR) and signal to noise ratio (SNR) analyses were performed for comparison of two detection systems. MTF curves and bar pattern images revealed an improvement of about 40% in the cutoff resolution with the PCD. The excellent spatial resolution offered by PCD system complemented superior detection of the diffraction fringes at boundaries of the acrylic edge and resulted in an EEI value of 3.64 as compared to 1.44 produced with EID image. At equal MGD levels (standard dose), observer studies along with CNR and SNR analyses revealed a substantial improvement of PCD acquired images in detection of simulated tumors, calcification clusters, and fibrous structures. At 30% less MGD, PCD images preserved image quality to yield equivalent (slightly better) detection as compared to the standard dose EID images. CdTe-based PCDs are technically feasible to image breast abnormalities (low/high contrast structures) at low radiation dose levels using the high energy inline phase sensitive imaging technique.

Recent advances in photon counting detection technology have led to significant research interest in X-ray imaging. As a tutorial level review, this paper covers a wide range of aspects related to X-ray photon counting detector characterization. The tutorial begins with a detailed description of the working principle and operating modes of a pixelated X-ray photon counting detector with basic architecture and detection mechanism. Currently available methods and techniques for charactering major aspects including energy response, noise floor, energy resolution, count rate performance (detector efficiency), and charge sharing effect of photon counting detectors are comprehensively reviewed. Other characterization aspects such as point spread function (PSF), line spread function (LSF), contrast transfer function (CTF), modulation transfer function (MTF), noise power spectrum (NPS), detective quantum efficiency (DQE), bias voltage, radiation damage, and polarization effect are also remarked. A cadmium telluride (CdTe) pixelated photon counting detector is employed for part of the characterization demonstration and the results are presented. This review can serve as a tutorial for X-ray imaging researchers and investigators to understand, operate, characterize, and optimize photon counting detectors for a variety of applications.

— At the Department of Physics of the University of Pisa and INFN of Pisa, we have assembled a high-resolution CT scanner prototype for small animals. The prototype will be integrated with the YAP-(S)PET scanner, in order to realize a combined PET\SPECT\CT scanner for small animals. We have characterized the microCT scanner prototype in terms of spatial resolution and noise using three different X-ray detectors. The first detector (Hamamatsu S7199) is composed by a CsI:Tl layer coupled to a CCD via a 1:1 fiber optic plate; the second detector (Radicon Rad-Eye 4) consists in a flat-panel CMOS sensor, directly coupled to a Ga2O2S:Tb scintillator; the third detector is a 1mm thick Si detector, bump-bonded to the Medipix2 readout chip. The first two detectors are based on indirect conversion of X-rays and operate in charge integration mode, while the third is a direct conversion detector and operates in photon counting mode. The characterization was carried out using dedicated phantoms for the measurement of spatial resolution and image noise. The results obtained with the three detectors are compared, in order to evaluate the differences in tomographic performances due to the different characteristics of each detector.

CMOS imagers based on Active Pixel Sensors (APS) are very important among others because of their possible technical innovations leading to ultra-low power image acquisition or efficient on-chip image preprocessing. Implementation of the image processing tasks (focal plane preprocessing and subsequent image processing) can be done effectively only with the consideration of known transfer characteristics of the imager itself. Geometrical Point Spread Function (PSF) depends on the certain geometric shape of active area in the particular design of CMOS APS. In this paper, the concept of Modulation Transfer Function (MTF) analysis is generalized to be applicable to the sampled structures of CMOS APS. Recalling theoretical results, we have analytically derived the detector MTF in the closed form for some special active area shapes. The paper also deals with the method based on pseudorandom image pattern with uniform power spectral density (PSD). This method allows to evaluate (in contrast to other methods) spatially invariant MTF including sampling MTF. It is generally known that a signal acquired by image sensor contains different types of noises. The superposition of these noises produces noise with a Gaussian distribution. The denoising method based on Bayesian estimator for implementation into the smart imager is presented.

Rapid development of the X-ray phonon-counting detection technology brings tremendous research and application opportunities. In addition to improvements in conventional X-ray imaging performance such as radiation dose utilization and beam hardening correction, photon-counting detectors allows significantly more efficient X-ray fluorescence (XRF) and K-edge imaging, and promises a great potential of X-ray functional, cellular and molecular imaging. XRF is the characteristic emission of secondary X-ray photons from a material excited by initial X-rays. The phenomenon is widely used for chemical and elemental analysis. K-edge imaging identifies a material based on its chemically-specific absorption discontinuity over X-ray photon energy. In this paper, we try to combine XRF and K-edge signals from the contrast agents (e.g., iodine, gadolinium, gold nanoparticles) to simultaneously realize XFCT and K-edge CT imaging for superior image performance. As a prerequisite for this dual-modality imaging, the accurate energy calibration of multi-energy-bin photon-counting detectors is critically important. With the measured XRF data of different materials, we characterize the energy response function of a CZT detector for energy calibration and spectrum reconstruction, which can effectively improve the energy resolution and decrease the inconsistence of the photon counting detectors. Then, a simultaneous K-edge and X-ray fluorescence CT imaging (SKYFI) experimental setup is designed which includes a cone-beam X-ray tube, two separate photon counting detector arrays, a pin-hole collimator and a rotation stage. With a phantom containing gold nanoparticles the two types of XFCT and K-edge CT datasets are collected simultaneously. Then, XFCT and K-edge CT images are synergistically reconstructed in a same framework. Simulation results are presented and quantitative analyzed and compared with the separate XFCT and K-edge CT results.

We present a novel time-resolved photon counting imaging technique and its use in multi-dimensional luminescence spectroscopy. By using an ultrafast camera coupled to an image intensifier on a microscope, we demonstrate the potential of wide-field time-correlated single photon counting, with a count rate of up to 5 Mhz. This system has the advantage of allowing the detection of single photons in parallel in every pixel. We measured the luminescence decay of Europium Polyoxometalate (POM), and observed contrast on lifetime images of Eu-POM on silver nanocrystals.

Effective detective quantum efficiency (eDQE) describes the resolution and noise properties of an imaging system along with scatter and primary transmission, all measured under clinically appropriate conditions. Effective dose efficiency (eDE) is the eDQE normalised to mean glandular dose and has been proposed as a useful metric for the optimisation of clinical imaging systems. The aim of this study was to develop a methodology for measuring eDQE and eDE on a Philips microdose mammography (MDM) L30 photon counting scanning system, and to compare performance with two conventional flat panel systems.A custom made lead-blocker was manufactured to enable the accurate determination of dose measurements, and modulation transfer functions were determined free-in-air at heights of 2, 4 and 6 cm above the breast support platform. eDQE were calculated for a Philips MDM L30, Hologic Dimensions and Siemens Inspiration digital mammography system for 2, 4 and 6 cm thick poly(methyl methacrylate) (PMMA). The beam qualities (target/filter and kilovoltage) assessed were those selected by the automatic exposure control, and anti-scatter grids were used where available.Measurements of eDQE demonstrate significant differences in performance between the slit- and scan-directions for the photon counting imaging system. MTF has been shown to be the limiting factor in the scan-direction, which results in a rapid fall in eDQE at mid-to-high spatial frequencies. A comparison with two flat panel mammography systems demonstrates that this may limit image quality for small details, such as micro-calcifications, which correlates with a more conventional image quality assessment with the CDMAM phantom. eDE has shown the scanning photon counting system offers superior performance for low spatial frequencies, which will be important for the detection of large low contrast masses. Both eDQE and eDE are proposed as useful metrics that should enable optimisation of the Philips MDM L30.