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    Magnetic Particle Imaging Using Ferromagnetic Magnetization

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    Nanofluids, defined as fluids containing suspended solid nanoparticles, are potential systems for utilization in biomedical applications. Magnetic Particle Imaging (MPI) uses superparamagnetic nanofluids, e.g. a colloidal suspension of iron oxide particles. In this work a new biocompatible nanofluid based on pure and stable ferromagnetic carbon is investigated. Although this material has a relatively small value of coercive magnetic field, it does exhibit a true ferromagnetic behavior up to 300 K. We present results obtained from numerical investigations performed to calculate the impact of a ferromagnetic magnetization to the MPI signal chain. Moreover, by modeling ferromagnetic magnetization we prove here the general suitability of ferromagnetic materials for MPI. Due to the low saturation magnetization, however, MPI for ferromagnetic carbon will be possible only in the near future when realistic concentrations of the nanofluid ferromagnetic carbon will be experimentally obtainable

    Influence of 12-bit and 16-bit CT values of metals on dose calculation in radiotherapy using PRIMO, a Monte Carlo code for clinical linear accelerators

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    In this paper, the effect of computed tomography (CT) values of metals in 12-bit and 16-bit extended Hounsfield Unit (EHU) scale on dose calculations in radiotherapy treatment planning systems (TPS) were quantified. Dose simulations for metals in water environment were performed with the software PRIMO in 6MV photon mode. The depth dose profiles were analysed and the relative dose differences between the metals determined with 12-bit and 16-bit CT imaging, respectively, were calculated. Maximum dose differences of ΔAl= 3.0%, ΔTi= 4.5%, ΔCr= 6.2% and ΔCu= 11.6% were measured. In order to increase the accuracy of dose calculation on patients with implants, CT imaging in the EHU scale is recommended

    Design and first results of a phantom study on the suitability of iterative reconstruction for lung-cancer screening with low-dose computer tomography

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    In this research computer tomography (CT) iterative reconstruction (IR) algorithms are investigated, specifically the impact of their statistical and model-based strength on image quality in low-dose lung screening CT protocols in comparison to filtered back projection (FBP). It has been probed whether statistical, model-based IR in conjunction with low-dose, and ultra-low-dose protocols are suitable for lungcancer screening. To this end, artificial lung nodules shaped as spheres and spicules made from material with calibrated Hounsfield units (HU) were attached on marked positions in the lung structure of an anthropomorphic phantom. Nodule positions were selected by distinguished radiologists. The phantom with nodules was scanned on a CT Scanner using standard high contrast (SHC), low-dose (LD) and ultra low-dose (ULD) protocol. For reconstruction FBP and the IR algorithm ADMIRE at three different

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