SPECT/CT registration with the DCC and MC simulations for SPECT imaging

publi Vincent Breto

Monte Carlo validation of a mu-SPECT imaging system on the lightweight grid CiGri

à paraître dans Future Generation Computer SystemsMonte Carlo Simulations (MCS) are nowadays widely used in the field of nuclear medicine for system and algorithms designs. They are valuable for accurately reproducing experimental data, but at the expense of a long computing time. An efficient solution for shorter elapsed time has recently been proposed: grid computing. The aim of this work is to validate a small animal gamma camera MCS and to confirm the usefulness of grid computing for such a study. Good matches between measured and simulated data were achieved and a crunching factor up to 70 was attained on a lightweight campus grid

Towards an effective potential for the monomer, dimer, hexamer, solid and liquid forms of hydrogen fluoride

We present an attempt to build up a new two-body effective potential for hydrogen fluoride, fitted to theoretical and experimental data relevant not only to the gas and liquid phases, but also to the crystal. The model is simple enough to be used in Molecular Dynamics and Monte Carlo simulations. The potential consists of: a) an intra-molecular contribution, allowing for variations of the molecular length, plus b) an inter-molecular part, with three charged sites on each monomer and a Buckingham "exp-6" interaction between fluorines. The model is able to reproduce a significant number of observables on the monomer, dimer, hexamer, solid and liquid forms of HF. The shortcomings of the model are pointed out and possible improvements are finally discussed.Comment: LaTeX, 24 pages, 2 figures. For related papers see also http://www.chim.unifi.it:8080/~valle

Speedup and Efficiency of Large Size Applications on Heterogeneous Networks

Program environments are now commonly used for parallelism on networks of workstations. There is a need for simple and consistent tools to measure algorithm performance on heterogeneous networks. In this work we propose a generalization to heterogeneous networks of the classical efficiency formula E(N) = S(N)=N , where S(N) is the speedup on N processors. keywords parallelism, performance evaluation, speedup, efficiency, heterogeneous networks 1 1 Introduction Today's scientific problems need more and more computing power. The present trend in supercomputer architecture development is to design parallel machines with powerful processors of more than 1Gflops. Workstation networks belong to this class of supercomputers. Environments like CHARM [18], Parform [7], P4 [6], PVM [11, 14], appeared allowing users to consider their computer networks as a virtual parallel machine. Most people have access to networks of computers. Furthermore, their total power has apparently no limit and s..

Efficient Sampling on Coarse Grids in Tomography

In tomography we have to give an estimate of a function from a finite number of its intergrals along straight lines or on strips. Under very reasonable conditions, the interlaced sampling is well known to be the most efficient scheme for this problem. In this paper we examine some pertubations on the interlaced scheme. Using a theorem due to A. Faridani, we show that sampling on coarse grids leads to efficient schemes, allowing to consider a lot of different sampling geometries. Some of them could be in practice much more easily generated than the interlaced one. New efficient sampling schemes of the Radon transform are proposed. Numerical experiments in the case of integrals on strips show the efficiency of these new schemes

Dynamic tomography, mass preservation and ROI reconstruction

International audienceAbstract--In this paper we consider the mass preservation in dynamic tomography. We present an analytic compensation of deformations preserving the mass and the acquisition line geometry.We show 2D ROI reconstructions of truncated dynamic data

Comparison of Analytic and Algebraic Methods for Motion-Compensated Cone-Beam CT Reconstruction of the Thorax

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