Stephen T. Bell

Energy Calibration of the Pixels of Spectral X-ray Detectors

The energy information acquired using spectral X-ray detectors allows noninvasive identification and characterization of chemical components of a material. To achieve this, it is important that the energy response of the detector is calibrated. The established techniques for energy calibration are not practical for routine use in pre-clinical or clinical research environment. This is due to the requirements of using monochromatic radiation sources such as synchrotron, radio-isotopes, and prohibitively long time needed to set up the equipment and make measurements. To address these limitations, we have developed an automated technique for calibrating the energy response of the pixels in a spectral X-ray detector that runs with minimal user intervention. This technique uses the X-ray tube voltage (kVp) as a reference energy, which is stepped through an energy range of interest. This technique locates the energy threshold where a pixel transitions from not-counting (off) to counting (on). Similarly, we have developed a technique for calibrating the energy response of individual pixels using X-ray fluorescence generated by metallic targets directly irradiated with polychromatic X-rays, and additionally γ-rays from 241Am. This technique was used to measure the energy response of individual pixels in CdTe-Medipix3RX by characterizing noise performance, threshold dispersion, gain variation and spectral resolution. The comparison of these two techniques shows the energy difference of 1 keV at 59.5 keV which is less than the spectral resolution of the detector (full-width at half-maximum of 8 keV at 59.5 keV). Both techniques can be used as quality control tools in a pre-clinical multi-energy CT scanner using spectral X-ray detectors.

Reducing beam hardening effects and metal artefacts in spectral CT using Medipix3RX

This paper discusses methods for reducing beam hardening effects and metal artefacts using spectral x-ray information in biomaterial samples. A small-animal spectral scanner was operated in the 15 to 80 keV x-ray energy range for this study. We use the photon-processing features of a CdTe-Medipix3RX ASIC in charge summing mode to reduce beam hardening and associated artefacts. We present spectral data collected for metal alloy samples, its analysis using algebraic 3D reconstruction software and volume visualisation using a custom volume rendering software. The cupping effect and streak artefacts are quantified in the spectral datasets. The results show reduction in beam hardening effects and metal artefacts in the narrow high energy range acquired using the spectroscopic detector. A post-reconstruction comparison between CdTe-Medipix3RX and Si-Medipix3.1 is discussed. The raw data and processed data are made available (http://hdl.handle.net/10092/8851) for testing with other software routines.This paper discusses methods for reducing beam hardening effects using spectral data for biomaterial applications. A small-animal spectral scanner operating in the diagnostic energy range was used. We investigate the use of photon-processing features of the Medipix3RX ASIC in reducing beam hardening and associated artefacts. A fully operational charge summing mode was used during the imaging routine. We present spectral data collected for metal alloy samples, its analysis using algebraic 3D reconstruction software and volume visualisation using a custom volume rendering software. Narrow high energy acquisition using the photon-processing detector revealed substantial reduction in beam hardening effects and metal artefacts.

MARS spectral molecular imaging of lamb tissue: data collection and image analysis

Spectral molecular imaging is a new imaging technique able to discriminate and quantify different components of tissue simultaneously at high spatial and high energy resolution. Our MARS scanner is an x-ray based small animal CT system designed to be used in the diagnostic energy range (20–140 keV). In this paper, we demonstrate the use of the MARS scanner, equipped with the Medipix3RX spectroscopic photon-processing detector, to discriminate fat, calcium, and water in tissue. We present data collected from a sample of lamb meat including bone as an illustrative example of human tissue imaging. The data is analyzed using our 3D Algebraic Reconstruction Algorithm (MARS-ART) and by material decomposition based on a constrained linear least squares algorithm. The results presented here clearly show the quantification of lipid-like, water-like and bone-like components of tissue. However, it is also clear to us that better algorithms could extract more information of clinical interest from our data. Because we are one of the first to present data from multi-energy photon-processing small animal CT systems, we make the raw, partial and fully processed data available with the intention that others can analyze it using their familiar routines. The raw, partially processed and fully processed data of lamb tissue along with the phantom calibration data can be found at http://hdl.handle.net/10092/8531.

Spectral CT data acquisition with Medipix3.1

This paper describes the acquisition of spectral CT images using the Medipix3.1 in spectroscopic mode, in which the chip combines 2 × 2 pixel clusters to increase the number of energy thresholds and counters from 2 to 8. During preliminary measurements, it was observed that the temperature, DAC and equalisation stability of the Medipix3.1 outperformed the Medipix3.0, while maintaining similar imaging quality. In this paper, the Medipix3.1 chips were assembled in a quad (2 × 2) layout, with the four ASICs bump-bonded to a silicon semiconductor doped as an np-junction diode. To demonstrate the biological imaging quality that is possible with the Medipix3.1, an image of a mouse injected with gold nano-particle contrast agent was obtained. CT acquisition in spectroscopic mode was enabled and examined by imaging a customised phantom containing multiple contrast agents and biological materials. These acquisitions showed a limitation of imaging performance depending on the counter used. Despite this, identification of multiple materials in the phantom was demonstrated using an in-house material decomposition algorithm. Furthermore, gold nano-particles were separated from biological tissues and bones within the mouse by means of image rendering.

Spectrum measurement using Medipix3 in Charge Summing Mode

We have obtained first spectrum measurements on a Medipix3 detector with a cadmium telluride (CdTe) sensor using Charge Summing Mode (CSM). It will be shown that CSM in Medipix3 is capable of reducing the adverse effects of charge sharing and fluorescent x-rays of CdTe on the spectra recorded. The development of the Medipix All Resolution System (MARS) x-ray camera has allowed us to explore this novel pixel communication feature in Medipix3. Spectrum measurements in this work were carried out using a MARS camera consisting of a Medipix3 chip bump-bonded to a 1mm thick CdTe sensor layer. The characteristic peaks of the Am-241 source as well as the spectroscopic properties of the CdTe sensor material were depicted at a spatial resolution of 55 ?m. Furthermore, a connected component algorithm shows a silicon based Medipix3 is effective in reallocating spread charge into a single pixel.

MARS-MD: Rejection based image domain material decomposition

This paper outlines image domain material decomposition algorithms that have been routinely used in MARS spectral CT systems. These algorithms (known collectively as MARS-MD) are based on a pragmatic heuristic for solving the under-determined problem where there are more materials than energy bins. This heuristic contains three parts: (1) splitting the problem into a number of possible sub-problems, each containing fewer materials; (2) solving each sub-problem; and (3) applying rejection criteria to eliminate all but one sub-problems solution. An advantage of this process is that different constraints can be applied to each sub-problem if necessary. In addition, the result of this process is that solutions will be sparse in the material domain, which reduces crossover of signal between material images. Two algorithms based on this process are presented: the Segmentation variant, which uses segmented material classes to define each sub-problem; and the Angular Rejection variant, which defines the rejection criteria using the angle between reconstructed attenuation vectors.

submitter : Semi-analytic off-axis X-ray source model

Spectral computed tomography (CT) systems are employed with energy-resolving photon counting detectors. Incorporation of a spectrally accurate x-ray beam model in image reconstruction helps to improve material identification and quantification by these systems. Using an inaccurate x-ray model in spectral reconstruction can lead to severe image artifacts, one of the extreme cases of this is the well-known beam-hardening artifacts. An often overlooked spectral feature of x-ray beams in spectral reconstruction models is the angular dependence of the spectrum with reference to the central beam axis. To address these factors, we have developed a parameterized semi-analytical x-ray source model in the diagnostic imaging range (30-120 kVp) by applying regression techniques to data obtained from Monte Carlo simulations (EGSnrc). This x-ray beam model is generalized to describe the off-axis spectral information within ±17o along θ (vertical direction), ±5o along (horizontal direction) of the central axis, and can be parameterized for specific x-ray tube models. Comparisons of our model with those generated by SpekCalc, TOPAS, and IPEM78 at central axis show good agreement (within 2 %). We have evaluated the model with experimental data collected with a small animal spectral scanner.

Oblique fluorescence in a MARS scanner with a CdTe-Medipix3RX

The latest version of the MARS small bore scanner makes use of the Medipix3RX ASIC, bonded to a CdTe or CZT semi-conductor layer, to count x-ray photons and create a spectroscopic CT data set. The MARS imaging chain uses the energy-resolved 2D transmission images to construct quantitative 3D spectral and material images. To improve the spectral performance of the imaging system it is important that the energy response of the detector is well calibrated. A common methodology for energy calibration is to use x-ray fluorescence (XRF), due to its effective monochromatic nature. Oblique (off-axis) XRF can be measured in situ in the MARS small bore scanner. A monoatomic foil is placed in front of the x-ray source and off-axis XRF is measured. A key issue is identifying near optimal measurement positions that maximize the XRF signal while minimizing transmitted and scattered x-rays from the primary beam. This work shows the development of a theoretical model that is able to identify where in the detector plane XRF is maximum. We present: (1) a theoretical model that calculates the XRF photon distribution across the detector plane produced from illuminated foils attached to the scanners filter bar; (2) preliminary experimental measurements of the XRF distribution outside of the main beam taken with a CdTe-Medipix3RX detector; and (3) a comparison between the model and experiment. The main motivation behind creating this model is to identify the region in the detector plane outside of the main beam where XRF is at a maximum. This provides the optimum detector location for measuring a monochromatic XRF source with minimal polychromatic contamination for its use in per-pixel energy calibration of Medipix3RX detectors in MARS scanners.

Dosimetry for spectral molecular imaging of small animals with MARS-CT

The Medipix All Resolution Scanner (MARS) spectral CT is intended for small animal, pre-clinical imaging and uses an x-ray detector (Medipix) operating in single photon counting mode. The MARS system provides spectrometric information to facilitate differentiation of tissue types and bio-markers. For longitudinal studies of disease models, it is desirable to characterise the system’s dosimetry. This dosimetry study is performed using three phantoms each consisting of a 30 mm diameter homogeneous PMMA cylinder simulating a mouse. The imaging parameters used for this study are derived from those used for gold nanoparticle identification in mouse kidneys. Dosimetry measurement are obtained with thermo-luminescent Lithium Fluoride (LiF:CuMgP) detectors, calibrated in terms of air kerma and placed at different depths and orientations in the phantoms. Central axis TLD air kerma rates of 17.2 (± 0.71) mGy/min and 18.2 (± 0.75) mGy/min were obtained for different phantoms and TLD orientations. Validation measurements were acquired with a pencil ionization chamber, giving an air-kerma rate of 20.3 (±1) mGy/min and an estimated total air kerma of 81.2 (± 4) mGy for a 720 projection acquisition. It is anticipated that scanner design improvements will significantly decrease future dose requirements. The procedures developed in this work will be used for further dosimetry calculations when optimizing image acquisition for the MARS system as it undergoes development towards human clinical applications.

Segmentation enhances material analysis in multi-energy CT: A simulation study

A segmentation algorithm that assists material analysis in multi-energy computed tomography is presented. Segmentation is typically used in conjunction with quantitative material analysis algorithms (known as material decomposition) to increase the total number of materials which can be discriminated and quantified. The algorithm illustrated here identifies voxels (in the image domain) with one of three material classes: air, soft tissues and dense tissue or contrast pharmaceuticals. Two soft tissue materials are chosen (the most and the least attenuating soft tissues) to define the boundaries between the different material classes. The intensity (calculated from the multi-energy representation using the Euclidean norm) of each voxel is compared to the two boundary materials to determine which material class it belongs to. Unlike other intensity based segmentation methods this algorithm checks, using multi-variate confidence intervals (ellipsoids), whether each voxel is statistically distinguishable from the two boundary materials. If the voxels are not distinguishable then they are defaulted to the soft tissue class. An advantage of this segmentation method is that noise which passes through to the binary representations of each material class typically resemble salt and pepper noise, which is easily removed with a median filter. Simulations demonstrate that the algorithm can correctly allocate a variety of medically relevant soft tissue and non soft tissue materials to their correct material classes and that segmentation using multi-energy information can handle noisier data than when using single-energy information. The proposed algorithm is also successfully applied to a multi-energy CT scan taken using the MARS (Medipix All Resolution System) scanner.