Energy calibration of the Medipix-2 Quad MXR detector

The Medipix-2 Quad MXR detector is a recent version of the Medipix hybrid silicon pixel detector, which was developed at CERN. It combines four Medipix-2 chips with one common sensor chip. The photon processing x-ray detector will be incorporated into the Medipix All Resolution System (MARS) scanner, a 3D spectroscopic imaging system being developed by a collaboration of researchers from the University of Canterbury and the Canterbury District Health Board. This paper reports on a method developed to carry out an energy calibration for the Quad MXR detector

Medipix Imaging - evaluation of datasets with PCA

Spectral datasets of a watch and a fetal hand have been acquired with the energy-resolving 2D X-ray imaging detector Medipix-2. We applied principal component analysis (PCA) to evaluate the spectral information in the data. PCA is useful as it identifies the relevant information in a few derived variables that account for most of the variance of the dataset. A scattergram and cluster analysis allow us to group pixels with similar spectral characteristics. With our data, three derived variables display the most relevant information of the full dataset which can be represented in one RGB image. We have begun to apply this method to CT reconstructed slices to separate different materials. Our approach applies PCA to the energy domain and should not be confused with widely used applications of PCA in pattern recognition where it is applied to the spatial domain

Processing of Spectral X-ray Data Using Principal Components Analysis

The goal of this work was to develop a technique to enhance contrast within the spectral domain so that variation in spectral characteristics within an image could easily be identified. The motivation is that using x-ray photon counting detectors, such as Medipix-3, it is now possible to obtain large data sets of spectroscopic data. In particular there has been growing interest in spectral (multi-energy) computed tomography (CT) in the field on biomedical imaging. Principal components analysis (PCA) was used to enhance the spectral images in the energy domain and to identify of the number of independent patterns of spectral variation. The method differs from other forms of spectral analysis in that it requires no prior knowledge of the materials being imaged, it can be applied to large data sets, and it can give an estimate of the total variance in the spectral domain. PCA is a statistical technique for multi-dimensional data analysis. It seeks to find a few variables that describe a majority of the variance within a multi-variate system. For spectral image enhancement, PCA is applied in the energy domain to identify the number of independent attenuation profiles within the data [1,2]. In PCA formulation, each measured energy is considered as one variable, while each pixel or voxel is one measurement of possible spectra. PCA then seeks to find a few derived vectors (often called eigen-spectra) which describe the majority of variance within the measured spectra. Each voxel in spectral CT data is transformed from being described by its attenuation over a range of energies to being described by the relative contribution of eigen-spectra, with the first few eigen-spectra containing a majority of the variance in the original data. Calculating the eigenvectors from the full spectral data set can be done but the computational expense limits this approach to relatively small data sets. For this study PCA methods were adapted from face recognition. In particular, rather than finding eigen-spectra from the full data set which is computationally slow, eigen-spectra were found from a much smaller representative subset of the complete data. Having identified variance in the spectral domain it is possible to represent this as a series of images each representing one pattern of spectral variance. Alternatively it is possible to produce images which combine the spectral data with traditional intensity images. In this approach the colour space (chroma) is chosen so that vectors that describe the majority of variance are coded as individual colours (eg. Red, Green, Blue). The intensity (brightness/luma) is given by non-spectroscopic data. Using a Medipix based micro-CT scanner images were obtained of a mouse's thorax containing both iodine and barium (K-edges 2.5 keV apart). A pharmacological preparation of iodine was infused into the vascular system and a barium preparation was levaged into the bronchi. Four energy bin CT data was obtained. Initially, intensity (non-spectroscopic) data was used to perform CT reconstruction. Then each of the four energy bins were independently CT reconstructed to produce a 3 dimensional spectroscopic data set. PCA was applied in the energy domain. The three eigen-spectra that represent the most variance were used to produce colour (combined chroma and luma) images. This demonstrated that the calcium (bones), iodine (vascular), and barium (bronchi) are all distinguishable using this technique

Applying CERN’s detector technology to health: MARS Biomedical 3D spectroscopic x-ray imaging

New Zealand has benefited considerably from our links with the European Centre for Nuclear Research (CERN). We have been an associate member of CERN for 8 years, with projects in high energy physics theory, in the high energy physics Compact Muon Solenoid (CMS) experiment, and in technology development. In 2006 we joined the Medipix-3 Collaboration. We have installed Medipix detectors in the CMS Cavern for monitoring neutrons and ionising radiation. Our major effort has been to build Medipix detectors into a 3D x-ray scanner of our design. The scanner is dubbed Desktop MARS (Medipix All Resolution system) and provides energy selective images of small biological and pathology specimens. This paper reviews several matters. We look at the support given by the NZ government who have seen benefits in our involvement, including skill development, economic and commercial opportunities, and in overcoming the isolation of distance. We review NZ’s particular role in CMS where particle physics is a driver of new technology; We explore the opportunities arising from Medipix as the first photon processing detector. We first summarise the design of the Medipix detector and discuss likely benefits of spectroscopic imaging in clinical radiology. CERN and the Medpiox-3 Collaboration have licensed us to commercialise the technology for biomedical imaging of small animals and humans using the Medipix detector as the key tool for obtaining 3D computed tomography spectroscopic x-ray CT images. Finally we present some images of biological specimens taken with the MARS scanner, including initial spectroscopic images of mice

Calibration and operation of the 3D spectroscopic "MARS" scanner

The Medipix All Resolution System (MARS) is a 3D spectroscopic imaging CT scanner based on the Medipix photon processing x-ray detector. The Medipix hybrid silicon pixel detectors, which were developed at CERN, are capable of high spatial and temporal resolution. Images can be obtained at different energy thresholds offering the potential for spectroscopic x-ray analysis. The present desktop MARS scanner (Figure 1) was constructed through a collaboration of researchers from the University of Canterbury and the Canterbury District Health Board. Mechanical calibration procedures and image quality tests will be presented and the operation and the status of the scanner will be discussed

Construction and Operation of the MARS-CT Scanner

The aim of this project is to build a spectroscopic CT scanner capable of taking multiple energy CT images of small animal and pathology specimens. The current prototype scanner uses a conventional x-ray tube and a Medipix2 x-ray detector (developed by the European Organisation for Nuclear Research - CERN) that is capable of photon counting and energy discrimination. The scanner is referred to as the Medipix All Resolution System-CT (MARS-CT). We designed and constructed the gantry and control electronics so that the detector and x-ray tube could be rotated around an object of up to 100 mm diameter. Software was written to control the scanner and reconstruct the spectroscopic projection data into a 3D volume, using cone beam filtered back projection. The scanner successfully takes 3D images at 43 µm resolution. The use is able to define the energy ranges known as energy bins. The scanner's stability, accuracy and image quality was proven and tested. We successfully scanned a range of small objects including mice

Spectroscopic Contrast-agent imaging with the Medipix CT-Scanner “MARS”

The prototype MARS (Medipix All Resolution System) x-ray CT scanner provides spatial and energy resolution at the same time. It is currently operated at Christchurch Hospital to evaluate the clinical potential of spectroscopic images. The first datasets with a focus on contrast-agent imaging have been processed

MARS: a 3D Spectroscopic X-Ray Imaging Device Based on Medipix

A spectroscopic x-ray CT scanner, providing both spatial and energy resolution was built. Tomographic datasets from mice have been acquired to evaluate the potential benefits of spectroscopic imaging in biomedical applications