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].
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.
Spectral Computed Tomography (spectral CT) is a newly emerging, medical imaging modality. It extends CT by acquiring multiple datasets over different x-ray energy bins. As the x-ray absorption of materials is energy dependent, the energy bins together provide significantly more information about the composition of the subject.To exploit the full potential of spectral CT, there are many new image processing challenges including reconstruction, material decomposition, and visualization. This paper introduces the development of a unique reconstruction algorithm which fully exploits the nature of spectral CT data. A small application called mART was developed which implements a standard Simultaneous Algebraic Reconstruction Technique (SART). mART will form the basis for future research and development.We demonstrate that in its current form it produces reconstructions of superior quality to the commercial reconstruction package Octopus CT R ⃝ which is the standard software adopted by our team. In addition, future plans for the reconstruction algorithm will be discussed.
Medipix2 assemblies with Si and CdTe sensors have been characterized using poly-energetic x-ray sources. This work reports the results of inhomogeneities within the sensors;individual pixel sensitivity response and their saturation effects at higher photon fluxes over one hundred frames. At higher tube currents saturation of both sensors is observed. We have performed correction for these inhomogeneities on both sensors.CT images with CdTe-Medipix2 are presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.