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机构地区:[1]浙江大学生物医学工程与仪器学院,杭州310027
出 处:《中国图象图形学报(A辑)》2001年第2期103-110,共8页Journal of Image and Graphics
摘 要:概要地分析和评述了近年来三维医学图象可视化技术的发展 ,并主要从三维医学图象的分割标注、多模态医学图象的数据整合、体数据的绘制等 3个角度对三维医学图象的可视化技术进行了分类综述 ,同时介绍了各种算法的原理和最新进展 .由于医学图象可视化的目的是辅助医生了解生物内部组织的信息 ,因此除图象绘制技术外 ,组织及组织特性的精确自动分割标注技术 ,以及将不同图象模态提供的互补信息综合起来的匹配 /融合技术 ,都是医学图象可视化需要解决的重要问题 ,其中 。The purpose of this paper is to present a survey of recent publications concerning visualization of medical images. These techniques are described in three profiles: segmentation and classification of 3D medical images, data integration of multimodality images, and rendering of volume data. The three catalogs of methods are classified and several specific examples of each class of algorithm are described. Many researchers are dealing with the problem of non invasive diagnosis. One way of doing this are the imaging techniques used in almost every clinical environment, e.g. Ultrasonography, X ray Computed Tomography(CT), Magnetic Resonance Imaging(MRI), fMRI, Positron Emission Tomography(PET), Single Photon Emission Tomography(SPET), ect. Segmentation aims at the location of segments of interest in the image and thus the partitioning of the image. The purpose of data integration is to combine image information from multiple modalities/protocols. Besides rendering, accurate and automatic segmentation and image registration/fusion techniques are both key problems in medical visualization. The visualization of multimodality images is the most challenging and promising direction in the field of three dimensional medical image visualization.
关 键 词:三维医学图象 多模态医学图象 可视化 图象分割 数据整合 图象匹配 数据融合 影像诊断
分 类 号:R445[医药卫生—影像医学与核医学] TP391.41[医药卫生—诊断学]
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