Fast and robust ray casting algorithms for virtual X-ray imaging

Freud, N.; Duvauchelle, Philippe; Létang, Jean Michel; Babot, D.

doi:10.1016/j.nimb.2006.03.009

Cited by 46 publications

(36 citation statements)

References 6 publications

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“…There are two main classes of X-ray simulation algorithms. The first approach is probabilistic and based on Monte Carlo trials [3], while the second is determinist or analytic, based on ray-tracing [14] (these include solving the Boltzmann transport equation [17]). …”

Section: X-ray Simulationmentioning

confidence: 99%

“…Radiation attenuation is computed by considering the amount of penetration of a ray into the object. Freud et al proposed a modified version of the Z-buffer, known as the L-buffer (for length buffer), to store the length of a ray crossing a given 3D object [14].…”

Section: X-ray Simulationmentioning

confidence: 99%

“…In [37], we demonstrated that this can be achieved using a GPU-implementation based on the L-buffer technique. In [14] and in [25], two algorithms were proposed to handle artefacts due to robustness issues in the L-buffer, but these methods are not efficiently applicable on the GPU. We proposed an alternative method using an adaptive filtering to solve this problem.…”

Section: X-ray Simulationmentioning

confidence: 99%

“…To efficiently compute the path length (L p ) of a ray through an object, we use Freud et al's Lbuffer algorithm [14]. For each scanned object an image (or L-buffer) is produced.…”

Section: The L-buffer Principlementioning

confidence: 99%

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Development and validation of real-time simulation of X-ray imaging with respiratory motion

Vidal

Villard

2016

Computerized Medical Imaging and Graphics

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soft tissue modelling and ray tracing on GPU to simultaneously compute the respiratory motion and X-ray imaging in real-time. Our aim is to provide validated building blocks with high fidelity to closely match both the human physiology and the physics of X-rays. A CPU-based set of algorithms is presented to model organ behaviours during respiration. Soft tissue deformation is computed with an extension of the Chain Mail method. Rigid elements move according to kinematic laws. A GPU-based surface rendering method is proposed to compute the X-ray image using the Beer-Lambert law. It is provided as an open-source library. A quantitative validation study is provided to objectively assess the accuracy of both components: i) the respiration against anatomical data, and ii) the X-ray against the Beer-Lambert law and the results of Monte Carlo simulations. Our implementation can be used in various applications, such as interactive medical virtual environment to train percutaneous transhepatic cholangiography in interventional radiology, 2D/3D registration, computation of digitally reconstructed radiograph, simulation of 4D sinograms to test tomography reconstruction tools.}, pmid = {to appear}, publisher = {Elsevier} } AbstractWe present a framework that combines evolutionary optimisation, soft tissue modelling and ray tracing on GPU to simultaneously compute the respiratory motion and X-ray imaging in real-time. Our aim is to provide validated building blocks with high fidelity to closely match both the human physiology and the physics of X-rays. A CPU-based set of algorithms is presented to model organ behaviours during respiration. Soft tissue deformation is computed with an extension of the Chain Mail method. Rigid elements move according to kinematic laws. A GPU-based surface rendering method is proposed to compute the X-ray image using the Beer-Lambert law. It is provided as an open-source library. A quantitative validation study is provided to objectively assess the accuracy of both components: i) the respiration against anatomical data, and ii) the X-ray against the Beer-Lambert law and the results of Monte Carlo simulations. Our implementation can be used in various applications, such as interactive medical virtual environment to train percutaneous transhepatic cholangiography in interventional radiology, 2D/3D registration, computation of digitally reconstructed radiographs, simulation of 4D sinograms to test tomography reconstruction tools.

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Section: X-ray Simulationmentioning

confidence: 99%

Section: X-ray Simulationmentioning

confidence: 99%

Section: X-ray Simulationmentioning

confidence: 99%

“…To efficiently compute the path length (L p ) of a ray through an object, we use Freud et al's Lbuffer algorithm [14]. For each scanned object an image (or L-buffer) is produced.…”

Section: The L-buffer Principlementioning

confidence: 99%

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Development and validation of real-time simulation of X-ray imaging with respiratory motion

Vidal

Villard

2016

Computerized Medical Imaging and Graphics

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“…Several research groups have developed a simulation tool for X-ray imaging for different purposes, e.g. VXI [5,6,7,8,9], XRayImagingSimulator [10,11,12], ScorpiusXLab [13], XRSIM [14], etc. However, most of these tools are developed in-house to meet specific needs for their own research and are not readily available.…”

Section: Introductionmentioning

confidence: 99%

A realistic projection simulator for laboratory based X-ray micro-CT

Dhaene

Pauwels

Schryver

et al. 2015

Nuclear Instruments and Methods in Physics Research Section B:

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In X-ray Computed Tomography (CT) each voxel of the reconstructed image contains a calculated grey value which represents the linear attenuation coefficient for the materials in that voxel. Conventional laboratory based CT scanners use polychromatic X-ray sources and integrating detectors with an energy dependent efficiency. Consequently the reconstructed attenuation coefficients will depend on the spectrum of the source and the spectral sensitivity of the detector. Beam hardening will alter the spectrum significantly as the beam propagates through the sample. Therefore, sample composition and shape will affect the reconstructed attenuation coefficients as well. A polychromatic projection simulator has been developed at the "Centre for X-ray Tomography" of the Ghent University (UGCT) which takes into account the aforementioned variables, allowing for complete and realistic simulations of CT scans for a wide range of geometrical setups. Monte Carlo simulations of the X-ray tubes and detectors were performed to model their spectral behaviour. In this paper, the implementation and features of the program are discussed. Simulated and real CT scans are compared to demonstrate the quantitative correctness of the simulations. Experiments performed at two different UGCT scanners yield a maximum deviation of 3.9% and 6.5% respectively, between the measured and simulated reconstructed attenuation coefficients.

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