• Journal of KIISE:Computer Systems and Theory
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• v.27 no.8
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• pp.691-700
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• 2000

The standard volume ray-tracing, optimized with octree, needs to repeatedly traverse hierarchical structures for each ray that often leads to redundant computations. It also employs the expensive 3D interpolation for producing high quality images. In this paper, we present a new ray-casting method that efficiently computes shaded colors and opacities at resampling points by traversing octree only once. This method traverses volume data in object-order, finds resampling points on slices incrementally, and performs resampling based on 2D interpolation. While the early ray-termination, which is one of the most effective optimization techniques, is not easily combined with object-order methods, we solved this problem using a dynamic data structure in image space. Considering that our new method is easy to implement, and need little additional memory, it will be used as very effective volume method that fills the performance gap between ray-casting and shear-warping.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.589-600
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• 2002

Deformable models offer an attractive approach for extracting three-dimensional boundary structures from volumetric images. However, conventional deformable models have three major limitations - sensitive to initial condition, difficult to represent complex boundaries with severe object concavities and protrusions, and self-intersective between model elements. This paper proposes a deformable model that is effective to extract geometrically complex boundary surfaces by improving away the limitations of conventional deformable models. First, the proposed deformable model resamples its elements hierarchically based on volume image pyramid. The hierarchical resampling overcomes sensitivity to initialization by extracting the boundaries of objects in a multiscale scheme and enhances geometric flexibility to be well adapted to complex image features by refining and regularizing the size of model elements based on voxel size. Second, the physics-based formulation of our model integrates conventional internal and external forces, as well as a non-self-intersecting force. The non-self-intersecting force effectively prevents collision or crossing over between non-neighboring model elements by pushing each other apart if they are closer than a limited distance. We show that the proposed model successively extracts the complex boundaries including severe concavities and protrusions, neither depending on initial position nor causing self-intersection, through the experiments on several computer-generated volume images and brain MR volume images.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.495-500
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• 2012

We consider a Bayesian test of independence in a two-way contingency table that has some zero cells. To do this, we take a three-stage hierarchical Bayesian model under each hypothesis. For prior, we use Dirichlet density to model the marginal cell and each cell probabilities. Our method does not require complicated computation such as a Metropolis-Hastings algorithm to draw samples from each posterior density of parameters. We draw samples using a Gibbs sampler with a grid method. For complicated posterior formulas, we apply the Monte-Carlo integration and the sampling important resampling algorithm. We compare the values of the Bayes factor with the results of a chi-square test and the likelihood ratio test.