8,716 research outputs found
Monte Carlo Simulation for Polychromatic X-ray Fluorescence Computed Tomography with Sheet-Beam Geometry
X-ray fluorescence computed tomography based on sheet-beam can save a huge
amount of time to obtain a whole set of projections using synchrotron. However,
it is clearly unpractical for most biomedical research laboratories. In this
paper, polychromatic X-ray fluorescence computed tomography with sheet-beam
geometry is tested by Monte Carlo simulation. First, two phantoms (A and B)
filled with PMMA are used to simulate imaging process through GEANT 4. Phantom
A contains several GNP-loaded regions with the same size (10 mm) in height and
diameter but different Au weight concentration ranging from 0.3% to 1.8%.
Phantom B contains twelve GNP-loaded regions with the same Au weight
concentration (1.6%) but different diameter ranging from 1mm to 9mm. Second,
discretized presentation of imaging model is established to reconstruct more
accurate XFCT images. Third, XFCT images of phantom A and B are reconstructed
by fliter backprojection (FBP) and maximum likelihood expectation maximization
(MLEM) with and without correction, respectively. Contrast to noise ratio (CNR)
is calculated to evaluate all the reconstructed images. Our results show that
it is feasible for sheet-beam XFCT system based on polychromatic X-ray source
and the discretized imaging model can be used to reconstruct more accurate
images
GATE : a simulation toolkit for PET and SPECT
Monte Carlo simulation is an essential tool in emission tomography that can
assist in the design of new medical imaging devices, the optimization of
acquisition protocols, and the development or assessment of image
reconstruction algorithms and correction techniques. GATE, the Geant4
Application for Tomographic Emission, encapsulates the Geant4 libraries to
achieve a modular, versatile, scripted simulation toolkit adapted to the field
of nuclear medicine. In particular, GATE allows the description of
time-dependent phenomena such as source or detector movement, and source decay
kinetics. This feature makes it possible to simulate time curves under
realistic acquisition conditions and to test dynamic reconstruction algorithms.
A public release of GATE licensed under the GNU Lesser General Public License
can be downloaded at the address http://www-lphe.epfl.ch/GATE/
Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation
Recently, X-ray imaging dose from computed tomography (CT) or cone beam CT
(CBCT) scans has become a serious concern. Patient-specific imaging dose
calculation has been proposed for the purpose of dose management. While Monte
Carlo (MC) dose calculation can be quite accurate for this purpose, it suffers
from low computational efficiency. In response to this problem, we have
successfully developed a MC dose calculation package, gCTD, on GPU architecture
under the NVIDIA CUDA platform for fast and accurate estimation of the x-ray
imaging dose received by a patient during a CT or CBCT scan. Techniques have
been developed particularly for the GPU architecture to achieve high
computational efficiency. Dose calculations using CBCT scanning geometry in a
homogeneous water phantom and a heterogeneous Zubal head phantom have shown
good agreement between gCTD and EGSnrc, indicating the accuracy of our code. In
terms of improved efficiency, it is found that gCTD attains a speed-up of ~400
times in the homogeneous water phantom and ~76.6 times in the Zubal phantom
compared to EGSnrc. As for absolute computation time, imaging dose calculation
for the Zubal phantom can be accomplished in ~17 sec with the average relative
standard deviation of 0.4%. Though our gCTD code has been developed and tested
in the context of CBCT scans, with simple modification of geometry it can be
used for assessing imaging dose in CT scans as well.Comment: 18 pages, 7 figures, and 1 tabl
Validation of the GATE Monte Carlo simulation platform for modelling a CsI(Tl) scintillation camera dedicated to small animal imaging
Monte Carlo simulations are increasingly used in scintigraphic imaging to
model imaging systems and to develop and assess tomographic reconstruction
algorithms and correction methods for improved image quantitation. GATE (GEANT
4 Application for Tomographic Emission) is a new Monte Carlo simulation
platform based on GEANT4 dedicated to nuclear imaging applications. This paper
describes the GATE simulation of a prototype of scintillation camera dedicated
to small animal imaging and consisting of a CsI(Tl) crystal array coupled to a
position sensitive photomultiplier tube. The relevance of GATE to model the
camera prototype was assessed by comparing simulated 99mTc point spread
functions, energy spectra, sensitivities, scatter fractions and image of a
capillary phantom with the corresponding experimental measurements. Results
showed an excellent agreement between simulated and experimental data:
experimental spatial resolutions were predicted with an error less than 100 mu
m. The difference between experimental and simulated system sensitivities for
different source-to-collimator distances was within 2%. Simulated and
experimental scatter fractions in a [98-182 keV] energy window differed by less
than 2% for sources located in water. Simulated and experimental energy spectra
agreed very well between 40 and 180 keV. These results demonstrate the ability
and flexibility of GATE for simulating original detector designs. The main
weakness of GATE concerns the long computation time it requires: this issue is
currently under investigation by the GEANT4 and the GATE collaboration
Development of advanced geometric models and acceleration techniques for Monte Carlo simulation in Medical Physics
Els programes de simulació Monte Carlo de caràcter general s'utilitzen actualment en una gran varietat d'aplicacions.Tot i això, els models geomètrics implementats en la majoria de programes imposen certes limitacions a la forma dels objectes que es poden definir. Aquests models no són adequats per descriure les superfícies arbitràries que es troben en estructures anatòmiques o en certs aparells mèdics i, conseqüentment, algunes aplicacions que requereixen l'ús de models geomètrics molt detallats no poden ser acuradament estudiades amb aquests programes.L'objectiu d'aquesta tesi doctoral és el desenvolupament de models geomètrics i computacionals que facilitin la descripció dels objectes complexes que es troben en aplicacions de física mèdica. Concretament, dos nous programes de simulació Monte Carlo basats en PENELOPE han sigut desenvolupats. El primer programa, penEasy, utilitza un algoritme de caràcter general estructurat i inclou diversos models de fonts de radiació i detectors que permeten simular fàcilment un gran nombre d'aplicacions. Les noves rutines geomètriques utilitzades per aquest programa, penVox, extenen el model geomètric estàndard de PENELOPE, basat en superfícices quàdriques, per permetre la utilització d'objectes voxelitzats. Aquests objectes poden ser creats utilitzant la informació anatòmica obtinguda amb una tomografia computeritzada i, per tant, aquest model geomètric és útil per simular aplicacions que requereixen l'ús de l'anatomia de pacients reals (per exemple, la planificació radioterapèutica). El segon programa, penMesh, utilitza malles de triangles per definir la forma dels objectes simulats. Aquesta tècnica, que s'utilitza freqüentment en el camp del disseny per ordinador, permet representar superfícies arbitràries i és útil per simulacions que requereixen un gran detall en la descripció de la geometria, com per exemple l'obtenció d'imatges de raig x del cos humà.Per reduir els inconvenients causats pels llargs temps d'execució, els algoritmes implementats en els nous programes s'han accelerat utilitzant tècniques sofisticades, com per exemple una estructura octree. També s'ha desenvolupat un paquet de programari per a la paral·lelització de simulacions Monte Carlo, anomentat clonEasy, que redueix el temps real de càlcul de forma proporcional al nombre de processadors que s'utilitzen.Els programes de simulació que es presenten en aquesta tesi són gratuïts i de codi lliures. Aquests programes s'han provat en aplicacions realistes de física mèdica i s'han comparat amb altres programes i amb mesures experimentals.Per tant, actualment ja estan llestos per la seva distribució pública i per la seva aplicació a problemes reals.Monte Carlo simulation of radiation transport is currently applied in a large variety of areas. However, the geometric models implemented in most general-purpose codes impose limitations on the shape of the objects that can be defined. These models are not well suited to represent the free-form (i.e., arbitrary) shapes found in anatomic structures or complex medical devices. As a result, some clinical applications that require the use of highly detailed phantoms can not be properly addressed.This thesis is devoted to the development of advanced geometric models and accelration techniques that facilitate the use of state-of-the-art Monte Carlo simulation in medical physics applications involving detailed anatomical phantoms. To this end, two new codes, based on the PENELOPE package, have been developed. The first code, penEasy, implements a modular, general-purpose main program and provides various source models and tallies that can be readily used to simulate a wide spectrum of problems. Its associated geometry routines, penVox, extend the standard PENELOPE geometry, based on quadric surfaces, to allow the definition of voxelised phantoms. This kind of phantoms can be generated using the information provided by a computed tomography and, therefore, penVox is convenient for simulating problems that require the use of the anatomy of real patients (e.g., radiotherapy treatment planning). The second code, penMesh, utilises closed triangle meshes to define the boundary of each simulated object. This approach, which is frequently used in computer graphics and computer-aided design, makes it possible to represent arbitrary surfaces and it is suitable for simulations requiring a high anatomical detail (e.g., medical imaging).A set of software tools for the parallelisation of Monte Carlo simulations, clonEasy, has also been developed. These tools can reduce the simulation time by a factor that is roughly proportional to the number of processors available and, therefore, facilitate the study of complex settings that may require unaffordable execution times in a sequential simulation.The computer codes presented in this thesis have been tested in realistic medical physics applications and compared with other Monte Carlo codes and experimental data. Therefore, these codes are ready to be publicly distributed as free and open software and applied to real-life problems.Postprint (published version
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