The MARS research group has created a new version of their scanner for taking improved spectral CT datasets. This version of the scanner (MARS-CT-3) has taken the first Medipix3 CT images of a phantom. MARS-CT-3 incorporates a new gantry, new x-ray sources and the new MARS readout board, as well as the ability to connect gas lines to the specimen.The new gantry has improved mechanical rigidity and can perform scans faster. Magnification can be controlled by moving the detector and the x-ray source independently. The brighter x-ray source means images can be taken six times faster. Gas lines allow the user to control various environmental factors inside the scanner, such as temperature, or deliver oxygen and anaesthetics, providing the ability to do a full spectroscopic CT scan of a live sedated biological specimen, such as a mouse. The new MARS readout is able to read from all current chips from the Medipix family, has faster image downloading, and the use of up to six Medipix detectors in parallel on the same chip carrier. The use of Medipix3 chips allows for compensation of charge sharing via Charge Summing Mode.

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 photonprocessing 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 x-ray imaging using novel photon counting x-ray detectors (PCDs) with energy resolving abilities is capable of providing energy-selective images. PCDs have energy thresholds, enabling the classification of photons into multiple energy bins. The extra energy information provided may allow materials such as iodine and calcium, or water and fat to be distinguishable. The information content of spectral x-ray images, however, depends on how the photons are grouped together. In this work, we present a model to optimize energy windows for maximum material discrimination. Multivariate statistics allows the confidence region of the correlated uncertainties to be mapped in the thickness space. Minimization of the uncertainties enables optimization of energy windows. Applications related to small animal imaging and breast imaging are considered.

The Medipix3 x-ray imaging detector has been characterized using the MARS camera. This x-ray camera comprises custom built readout electronics and software libraries designed for the Medipix family of detectors. The performance of the Medipix3 and MARS camera system is being studied prior to use in real-world applications such as the recently developed MARS-CT3 spectroscopic micro-CT scanner. We present the results of characterization measurements, describe methods for optimizing performance and give examples of spectroscopic images acquired with Medipix3 and the MARS camera system.A limited number of operating modes of the Medipix3 chip have been characterized and singlepixel mode has been found to give acceptable performance in terms of energy response, image quality and stability over time. Spectroscopic performance is significantly better in charge-summing mode than single-pixel mode however image quality and stability over time are compromised. There are more modes of operation to be tested and further work is required to optimize the performance of the chip.

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.