• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.9-20
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• 2010

In order to visualize participating media in 3D space, they usually calculate the incoming radiance by subdividing the ray path into small subintervals, and accumulating their respective light energy due to direct illumination, scattering, absorption, and emission. Among these light phenomena, scattering behaves in very complicated manner in 3D space, often requiring a great deal of simulation efforts. To effectively simulate the light scattering effect, several approximation techniques have been proposed. Volume photon mapping takes a simple approach where the light scattering phenomenon is represented in volume photon map through a stochastic simulation, and the stored information is explored in the rendering stage. While effective, this method has a problem that the number of necessary photons increases very fast when a higher variance reduction is needed. In an attempt to resolve such problem, we propose a different approach for rendering particle-based volume data where kernel smoothing, one of several density estimation methods, is explored to represent and reconstruct the light in-scattering effect. The effectiveness of the presented technique is demonstrated with several examples of volume data.

• Journal of the Korea Computer Graphics Society
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• v.14 no.4
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• pp.7-18
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• 2008

To realistically produce fluids such as smoke for the visual effects in the films or animations, we need two main processes: a physics-based modeling of smoke and a rendering of smoke simulation data, based on light transport theory. In the computer graphics community, the physics-based fluids simulation is generally adopted for smoke modeling. Recently, the interest of the particle-based Lagrangian simulation methods is increasing due to the advantages at simulation time, instead of the grid-based Eulerian simulation methods which was widely used. As a result, because the smoke rendering technique depends heavily on the modeling method, the research for rendering of the particle-based smoke data still remains challenging while the research for rendering of the grid-based smoke data is actively in progress. This paper focuses on realistic rendering technique for the smoke particles produced by Lagrangian simulation method. This paper introduces a technique which is called particle map, that is the expansion and modification of photon mapping technique for the particle data. And then, this paper suggests the novel particle map technique and shows the differences and improvements, compared to previous work. In addition, this paper presents irradiance map technique which is the pre-calculation of the multiple scattering term in the volume rendering equation to enhance efficiency at rendering time.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1165-1176
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• 2010

In order to realistically visualize such participating media as cloud, smoke, and gas, the light transport process must be physically simulated inside the media. While it is known that this process is well described physically through the volume rendering equation, it usually takes a great deal of computation time for obtaining high-precision solutions. Recently, GPU-based, fast rendering methods have been proposed for the realistic simulation of participating media, however, there still remain several problems to be resolved. In this article, we describe our rendering techniques applied to enhance the performances and features of our GPU-assisted participating media renderer, and analyze how such efforts have actually improved the renderer. The presented techniques will be effectively used in volume renderers for creating various digital contents in the special effects industries.

• Progress in Medical Physics
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• v.24 no.4
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• pp.237-242
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• 2013

In the intracranial regions, an accurate delineation of the target volume has been difficult with only the CT data due to poor soft tissue contrast of CT images. Therefore, the magnetic resonance images (MRI) for the delineation of the target volumes were widely used. To calculate dose distributions with MRI-based RTP, the electron density (ED) mapping concept from the diagnostic CT images and the pseudo CT concept from the MRI were introduced. In this study, the look up table (LUT) from the fifteen patients' diagnostic brain MRI images was created to verify the feasibility of MRI-based RTP. The dose distributions from the MRI-based calculations were compared to the original CT-based calculation. One MRI set has ED information from LUT (lMRI). Another set was generated with voxel values assigned with a homogeneous density of water (wMRI). A simple plan with a single anterior 6MV one portal was applied to the CT, lMRI, and wMRI. Depending on the patient's target geometry for the 3D conformal plan, 6MV photon beams and from two to five gantry portals were used. The differences of the dose distribution and DVH between the lMRI based and CT-based plan were smaller than the wMRI-based plan. The dose difference of wMRI vs. lMRI was measured as 91 cGy vs. 57 cGy at maximum dose, 74 cGt vs. 42 cGy at mean dose, and 94 cGy vs. 53 at minimum dose. The differences of maximum dose, minimum dose, and mean dose of the wMRI-based plan were lower than the lMRI-based plan, because the air cavity was not calculated in the wMRI-based plan. These results prove the feasibility of the lMRI-based planning for brain tumor radiation therapy.