Christopher J. Bateman

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.

Discrimination Between Calcium Hydroxyapatite and Calcium Oxalate Using Multienergy Spectral Photon-Counting CT

OBJECTIVE We aimed to determine whether multienergy spectral photon-counting CT could distinguish between clinically relevant calcium crystals at clinical x-ray energy ranges. Energy thresholds of 15, 22, 29, and 36 keV and tube voltages of 50, 80, and 110 kVp were selected. Images were analyzed to assess differences in linear attenuation coefficients between various concentrations of calcium hydroxyapatite (54.3, 211.7, 808.5, and 1169.3 mg/cm3) and calcium oxalate (2000 mg/cm3). CONCLUSION The two lower concentrations of hydroxyapatite were distinguishable from oxalate at all energy thresholds and tube voltages, whereas discrimination at higher concentrations depended primarily on the energy thresholds used. Multienergy spectral photon-counting CT shows promise for distinguishing these calcium crystals.

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.

Discrimination of clinically significant calcium salts using MARS spectral CT

Calcium compounds within tissues are usually a sign of pathology, and calcium crystal type is often a pointer to the diagnosis. There are clinical advantages in being able to determine the quantity and type of calcifications non-invasively in cardiovascular, genitourinary and musculoskeletal disorders, and treatment differs depending on the crystal type and quantity. The problem arises when trying to distinguish between different calcium compounds within the same image due to their similar attenuation properties. There are spectroscopic differences between calcium salts at very low energies. As calcium oxalate and calcium hydroxyapatite can co-exist in breast and musculoskeletal pathologies of the breast, we wished to determine whether Spectral CT could distinguish between them in the same image at clinical X-ray energy ranges. Energy thresholds of 15, 22, 29 and 36keV and tube voltages of 50, 80 and 110kVp were chosen, and images were analysed to determine the percentage difference in the attenuation coefficients of calcium hydroxyapatite samples at concentrations of 54.3, 211.7, 808.5 and 1169.3mg/ml, and calcium oxalate at a concentration of 2000 mg/ml. The two lower concentrations of calcium hydroxyapatite were distinguishable from calcium oxalate at all energies and all tube voltages, whereas the ability to discriminate oxalate from hydroxyapatite at higher concentrations was dependent on the threshold energy but only mildly dependent on the tube voltage used. Spectral CT shows promise for distinguishing clinically important calcium salts.

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.

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.

Beam profile assessment in spectral CT scanners

Abstract In this paper, we present a method that uses a combination of experimental and modeled data to assess properties of x‐ray beam measured using a small‐animal spectral scanner. The spatial properties of the beam profile are characterized by beam profile shape, the angular offset along the rotational axis, and the photon count difference between experimental and modeled data at the central beam axis. Temporal stability of the beam profile is assessed by measuring intra‐ and interscan count variations. The beam profile assessment method was evaluated on several spectral CT scanners equipped with Medipix3RX‐based detectors. On a well‐calibrated spectral CT scanner, we measured an integral count error of 0.5%, intrascan count variation of 0.1%, and an interscan count variation of less than 1%. The angular offset of the beam center ranged from 0.8° to 1.6° for the studied spectral CT scanners. We also demonstrate the capability of this method to identify poor performance of the system through analyzing the deviation of the experimental beam profile from the model. This technique can, therefore, aid in monitoring the system performance to obtain a robust spectral CT; providing the reliable quantitative images. Furthermore, the accurate offset parameters of a spectral scanner provided by this method allow us to incorporate a more realistic form of the photon distribution in the polychromatic‐based image reconstruction models. Both improvements of the reliability of the system and accuracy of the volume reconstruction result in a better discrimination and quantification of the imaged materials.