• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.425-432
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• 2003

This paper presents an EMR(Electronic Medical Record) chart for efficient PDA through the quad tree image rendering based on the mobile. Using the intermediate image space algorithm instead of the final one for volume rendering, we have solved the probems of th eholes coming from the point-to-point to mapping. The quad-tree based on the delta-tree efficiently represents volume expressions and results in higher compression effects. With the volume rendering, we can decrease the rendering time and get a higher quality and efficiency for PDA through image based rendering.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.5
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• pp.286-299
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• 2006

Due to the continuing technical progress in the capabilities of modeling, simulation, and sensor devices, huge volume data with very high resolution are common. In scientific visualization, various interactive real-time techniques on high performance parallel computers to effectively render such large scale volume data sets have been proposed. In this paper, we present a mobile volume visualization system that consists of mobile clients, gateways, and parallel rendering servers. The mobile clients allow to explore the regions of interests adaptively in higher resolution level as well as specify rendering / viewing parameters interactively which are sent to parallel rendering server. The gateways play a role in managing requests / responses between mobile clients and parallel rendering servers for stable services. The parallel rendering servers visualize the specified sub-volume with rendering contexts from clients and then transfer the high quality final images back. This proposed system lets multi-users with PDA simultaneously share commonly interesting parts of huge volume, rendering contexts, and final images through CSCW(Computer Supported Cooperative Work) mode.

• Journal of the Korea Computer Graphics Society
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• v.21 no.3
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• pp.17-26
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• 2015

In this paper, we explain a volume rendering system for client-server environment. A single GPU-equipped PC works as a server which is based on the ideas that only a few concurrent users use a volume rendering system in a small hospital. As the clients, we used Android mobile devices such as smart phones. User events are transformed to rendering requests by the client application. When the server receives a rendering request, it renders the volume using the GPU. The rendered image is compressed to JPEG or PNG format so that we can save network bandwidth and reduce transfer time. In addition, we perform an event pruning method while a user is dragging the touch to enhance latency. The server compensates the pruning by interpolating the touch positions. As the result, real-time volume rendering is possible for 5 concurrent users on single GPU-equipped commodity hardware.

• Journal of the Korea Computer Graphics Society
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• v.8 no.1
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• pp.1-11
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• 2002

In order to widely use volume rendering technology in practical fields, a user should be able to control the classification parameter interactively and extract a meaningful information easily from the 3D data as fast as it can be. Previous work on an accelerating volume rendering reconstructs an isotropic volume from an anisotropic one and classifies in pre-processing time and then renders the classified volume rapidly in run time. But, this traditional step may result in long pre-processing time and no real-time feedback. In this paper, we present an efficient classification and rendering method that allows a user to set the opacity transfer function interactively at rendering time on a personal computer without special-purpose hardware.

• Journal of Korea Multimedia Society
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• v.18 no.5
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• pp.620-630
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• 2015

This research suggests a load balancing method for a volume rendering system which supports concurrent users. When concurrent users use a volume rendering server system, the computational resources are occupied by a particular user by turns because each process consumes the computational resources as much as possible. In this case, the previous method shows acceptable throughput but the latency is increased for each user. In this research, we suggest a method to improve the latency without performance degradation. Each process makes concessions for taking the resources according to the number of users connected to the system. And we propose a load balancing method in the dynamic situation in which the number of users can vary. Using our methods, we can improve the latency time for each user.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.662-665
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• 2005

본 논문에서는 체적 데이터에 대한 효율적인 볼륨 랜더링을 수행하기 위해서, 기존의 광선 추적 기법에 대해 광선 보간을 통해서 광선을 추적하는 기법인 IRCF를 제안한다. IRCF 과정은 이웃 화소에 대한 광선추적을 통해 얻은 불투명도값의 정보를 이용해 현재 광선 추적 위치와 불투명도값을 보간한 위치에서 새롭게 광선 추적을 해가는 방식이다. 기존의 고화질의 광선 추적 랜더링의 경우 Volume Rendering Operations의 계샨량이 많아 그 만큼 랜더링 속도가 떨어져 체적에 대해 다른 개선된 랜더링 기법들이 많이 제안되고 있다. 본 논문은 다른 각도로의 접근하고자 제안한 기법을 통해 Volume Rendering Operations의 계샨량을 최대한 줄임으로 랜더링 속도를 높이고 기본의 고화질 영상에 가까운 결과을 얻을 수가 있었다. 또한, 본 논문에서는 기존의 광선 추적 기법에서 표현하는 일반적인 회전, 절단, 불투명 등 제어 효과들을 제안한 기법을 통해 비교 분석한다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.213-216
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• 2000

본 논문에서는 volume rendering 기법을 이용하여 2차원 MRI 영상들을 합성하여 3차원 영상 만들 때 보다 해상도를 높이기 위한 개선된 sampling방법을 소개한다 2차원 슬라이스 영상들이 3차원으로 재구성할 때 voxel 기반으로 렌더링을 하기 때문에 오브젝트의 내부 영역까지도 볼 수 있는 것이 volume rendering의 가장 큰 장점이다. 따라서 영상을 재구성하는 과정에서 보다 향상된 interpolation을 적용시켜서 공간 해상도를 향상시키면 보다 명확하게 오브젝트 내부 정보를 살펴 볼 수 있다. 본 논문에서는 nearest neighbor 이나 linear 같은 interpolation으로 sampling한 방법보다 cubic interpolation을 3차원 공간에서 적용 시켜서 보다 resampling이 잘 되도록 하여 해상도를 향상시켜 보았다. 이렇게 향상된 Interpolation 적용시켜서 렌더링할 때 얼마나 오브젝트 내부 영역이 잘 가시화가 되었는지 transfer function을 적용시켜서 오브젝트 내부 정보를 렌더링 해보았고, 임의의 축으로 오브젝트을 잘라서 2D 단면 영상으로 출력해 보았다. 보다 향상된 interpolation을 적용시켜서 resampling을 하면 영상 해상도가 개선되었음을 볼 수 있었다.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.191-196
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• 2009

Volume rendering is a method which extracts meaningful information from volume data and visualizes those information. In general, since the size of volume data gets larger, it is very important to devise acceleration methods for interactive rendering speed. Min-max octree is data structure for high-speed volume rendering, however, its creation time becomes long as the data size increases. In this paper, we propose acceleration method of min-max octree generation using CUDA. Firstly, we convert one-dimensional array from volume data using space filling curve. Then we make min-max octree structures from the sequential array and apply them to acceleration of volume ray casting.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3280-3289
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• 2000

In this paper,we propose a novel technoque of improving volume rendering quality and speed by integrating volume data and global shape information together. The selective volume rendering method is to generate distance transformed volume using a distance transform to determine the minimum distance to the neaest intercsting part and then render it. The shape information prevents from object occlusions come from similar intensity of each object. Thus it provides effective visual results that enable to get a clear understanding of complex structures. We show the results of selective volume rendering method for left ventricle and right ventricle ans well as the results of selective sampling methods depending on the interpolation from EBCT cardiac images. Our method offers an accelerated technique to accurately visuahze the surfaces of devined objects segmented from the volume.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.35-42
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• 2018

Direct volume rendering (DVR) is an important 3D visualization method for medical images as it depicts the full volumetric data. However, because DVR renders the whole volume, regions of interests (ROIs) such as a tumor that are embedded within the volume maybe occluded from view. Thus, conventional 2D cross-sectional views are still widely used, while the advantages of the DVR are often neglected. In this study, we propose a new visualization algorithm where we augment the 2D slice of interest (SOI) from an image volume with volumetric information derived from the DVR of the same volume. Our occlusion-based DVR augmentation for SOI (ODAS) uses the occlusion information derived from the voxels in front of the SOI to calculate a depth parameter that controls the amount of DVR visibility which is used to provide 3D spatial cues while not impairing the visibility of the SOI. We outline the capabilities of our ODAS and through a variety of computer tomography (CT) medical image examples, compare it to a conventional fusion of the SOI and the clipped DVR.