| 血管分割可视化中的快速交互型渲染方法 |
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| 引用本文： | 杨新.血管分割可视化中的快速交互型渲染方法[J].上海大学学报(英文版),2008,12(3):240-248. |
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| 作者姓名： | 杨新 |
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| 作者单位： | MAXIME Guilbot（Institute of Image Processing and Patten Recognition, Shanghai Jiaotong University, Shanghai 200240, P. R. China.）
YANG Xin（Institute of Image Processing and Patten Recognition, Shanghai Jiaotong University, Shanghai 200240, P. R. China.） |
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| 基金项目： | 国家自然科学基金
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国家重点基础研究发展计划(973计划) |
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| 摘 要： |
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| 关 键 词： | volume rendering coronary vessels segmentation segmentation error detection texture shader graphic processing uint (GPU) 血管分割 可视化 快速 型体 渲染 方法 visualization segmentation vessel adjustable methods volume rendering shading functions recently introduced cards fast interact new algorithm |
| 收稿时间： | 2006-12-13 |
| 修稿时间： | 2006年12月13 |
Fast interactive volume rendering method for adjustable vessel segmentation visualization |
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| Guilbot?Maxime,Xin?Yang.Fast interactive volume rendering method for adjustable vessel segmentation visualization[J].Journal of Shanghai University(English Edition),2008,12(3):240-248. |
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| Authors: | Guilbot Maxime Xin Yang |
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| Institution: | Institute of Image Processing and Patten Recognition, Shanghai Jiaotong University, Shanghai 200240, P. R. China. |
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| Abstract: | Medical diagnosis software and computer-assisted surgical systems often use segmented image data to help clinicians make decisions. The segmentation extracts the region of interest from the background, which makes the visualization clearer. However, no segmentation method can guarantee accurate results under all circumstances. As a result, the clinicians need a solution that enables them to check and validate the segmentation accuracy as well as displaying the segmented area without ambiguities.With the method presented in this paper, the real CT or MR image is displayed within the segmented region and the segmented boundaries can be expanded or contracted interactively. By this way, the clinicians are able to check and validate the segmentation visually and make more reliable decisions. After experiments with real data from a hospital, the presented method is proved to be suitable for efficiently detecting segmentation errors. The new algorithm uses new graphic processing uint (GPU) shading functions recently introduced in graphic cards and is fast enough to interact on the segmented area, which was not possible with previous methods. |
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| Keywords: | volume rendering coronary vessels segmentation segmentation error detection texture shader graphic processing uint (GPU) |
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