Sukhyun Lim

Efficient Space-Leaping Using Optimal Block Sets

There are several optimization techniques available for improving rendering speed of direct volume rendering. An acceleration method using the hierarchical min-max map requires little preprocessing and data storage while preserving image quality. However, this method introduces computational overhead because of unnecessary comparison and level shift between blocks. In this paper, we propose an efficient space-leaping method using optimal-sized blocks. To determine the size of blocks, our method partitions an image plane into several uniform grids and computes the minimum and the maximum depth values for each grid. We acquire optimal block sets suitable for individual rays from these values. Experimental results show that our method reduces rendering time when compared with the previous min-max octree method.

A distance template for octree traversal in CPU-based volume ray casting

Several optimization techniques have been proposed to improve the speed of direct volume rendering. A hierarchical representation formed by an octree is a data structure to skip over transparent regions while requiring little preprocessing and data storage. However, in order to skip over an octant estimated to be transparent (a transparent octant), the distance from a boundary to another boundary of the octant should be calculated. Because the distance computation is expensive, we propose a precomputed data structure, the distance template, which stores direction and distance values from one boundary voxel on a face to all the boundary voxels on the remaining five faces. In the rendering step, if a ray reaches a transparent octant, it leaps over the octant by referring to the stored distance value.

Wearable Computer System Reflecting Spatial Context

We have a lot of interests to wearable computer as an IT technology has been advanced. Although aids for disabled persons are also developed variously, those for visually impaired persons were limited. In this study, we proposed a wearable system that can do walk safely to the destination for the visually impaired persons. Our system guides a user to arrive at destination using marker information detected by camera. Also it uses multiple ultrasonic sensors array to detect and avoid obstacles. After recognizing position and orientation of markers attached on the indoor ceiling, we can estimate relative direction to destination. At the same time, we simplify a complex spatial structure in front of user into some patterns by means of ultrasonic sensors and determine an avoidance direction by estimating the patterns. Our system helps users to arrive to destination safely without others help.

Reliable Space Leaping Using Distance Template

Several optimization techniques for direct volume rendering have been proposed since its rendering speed is too slow. An acceleration method using min-max map requires a little preprocessing and additional data structures while preserving image quality. However, we have to calculate accurate distance from current point to the boundary of a min-max block to skip over empty space. Unfortunately the cost for evaluating the distance is so expensive. In this paper, we propose reliable space leaping method to jump to the boundary of current block using pre-calculated distance template. A template can be reused for entire volume since it is independent on viewing conditions. Our algorithm reduced rendering time in comparison to conventional min-max map based volume ray casting.

Unfolding of virtual endoscopy using ray-template

Unfolding, one of virtual endoscopy techniques, gives us a flatten image of the inner surface of an organ. It is more suitable for a diagnosis and polyp detection. Most common unfolding methods use radial ray casting along with pre-computed central path. However, it may produce false images deformed and lost some information because adjacent ray planes cross when the organs curvature is relatively high. To solve it, several methods have been presented. However, these have severe computational overhead. We propose an efficient crossing-free ray casting for unfolding. It computes ray-cones according to curvature of the path. Then in order to avoid intersection between ray-cones, it adjusts direction of ray-cones detected while testing intersection. Lastly, it determines direction of all rays fired from sample points between control points by simple linear interpolation. Experimental results show that it produces accurate images of a virtually dissected colon and takes not much time.

A Half-Skewed Octree for Volume Ray Casting

A hierarchical representation formed by an octree for a volume ray casting is a well-known data structure to skip over transparent regions requiring little preprocessing and storage. However, it accompanies unnecessary comparison and level shift between octants. We propose a new data structure named half-skewed octree, which is an auxiliary octree to support the conventional octree. In preprocessing step, a half-skewed octree selects eight different child octants in each generation step compared with the conventional octree. During rendering, after comparing an octant of the conventional octree with corresponding octant of the half-skewed octree simultaneously at the same level, a ray chooses one of two octants to jump over transparent regions farther away. By this method, we can reduce unnecessary comparison and level shift between octants. Another problem of a conventional octree structure is that it is difficult to determine a distance from the boundary of a transparent octant to opposite boundary. Although we exploit the previously proposed distance template, we cannot expect the acceleration when a ray direction is almost parallel to the octants boundary. However, our method can solve it without additional operations because a ray selects one octant to leap farther away. As a result, our approach is much faster than the method using conventional octree while preserving image quality and requiring minimal storage.

Hierarchical σ-octree for visualization of ultrasound datasets

There are two important factors to visualize ultrasound datasets using volume ray casting method. Firstly, efficient methods to skip over empty space are required. Secondly, adequate noise-detection methods are necessary because ultrasound datasets contain lots of speckle noises. In general, space-leaping and noise-filtering methods are exploited to solve the problems. However, it increases the preprocessing time to generate the filtered datasets, and interesting (meaningful) objects could be affected by a filtering operation. We propose a hierarchical octree containing min-max values and standard deviation for each block, named a hierarchical σ–octree. In rendering step, our method refers to min-max values of a block. If the block is regarded as nontransparent, it also checks its standard deviation value to detect speckle noises. Our method reduces rendering time compared with the method using only the min-max values because most blocks containing speckle noises are considered as transparent.

A-PARM: Adaptive Division of Sub-cells in the PARM for Efficient Volume Ray Casting

The PARM is a data structure to ensure interactive frame rates on a PC platform for CPU-based volume ray casting. After determining candidate cells that contribute to the final images, it partitions each candidate cell into several sub-cells. Then, it stores trilinearly interpolated scalar value and an index of encoded gradient vector for each sub-cell. Since the information that requires time-consuming computations is already stored in the structure, the rendering time is reduced. However, it requires huge memory space because most precomputed values are loaded in the system memory. We solve it by adaptively dividing candidate cells into different sub-cells. That is, we divide a candidate cell in which the gradient is strictly changed into a large number of sub-cells, and vice versa. By this approach, we acquire moderate images while reducing the memory size.

Surface reconstruction for efficient colon unfolding

Unfolding is a new visualization method for colorectal disease and polyp detection. Compared with a virtual endoscopy method, it is more suitable for medical applications because it gives us unfold images of the inner surface in an organ. However, since conventional unfold methods generate only 2D images, it is difficult to show the surface at a first glance and to manage unfolding results with diverse viewing controls such as rotation and magnification. To solve it, we propose an efficient unfolding method using surface reconstruction. Firstly, we generate a 2D unfold image using volume ray casting. At the same time, we store distance values from each sample point on a central path to colon surface, for all rays. After making a height field from the distance values, we reconstruct a 3D surface model. Lastly, a 3D unfold image is acquired by mapping the 2D unfold image into the 3D surface model. Since our method offers the overall shape of an organ surface, the problematic areas can be identified quickly and inspected afterwards in more detail.

PARM: data structure for efficient volume ray casting

We propose a new data structure to accelerate the color computation step of CPU-based volume ray casting. To ensure interactive frame rates on a PC platform, we store interpolated scalar value and gradient vector required for color computation step in volume ray casting. However, it is difficult to store those two values in preprocessing step because sample points can lie in arbitrary position in a cell. Therefore, after determining candidate cells that contribute to the final images, we partition each candidate cell into several sub-cells. Then, we store trilinearly interpolated scalar value and an index of encoded gradient vector for each sub-cell. Because the information that requires time-consuming computations is already stored in our data structure, color values are determined without further computations.