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A multiresolution hierarchical approach to image segmentation based on intensity extrema

机译:基于强度极值的多分辨率分层图像分割方法

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A computer algorithm which segments gray-scale images into regions of interest (objects) has been developed. These regions can provide the basis for scene analysis (including shape-parameter calculation) or surface-based, shaded-graphics display. The algorithm creates a tree structure for image description by defining a linking relationship between pixels in successively blurred versions of the initial image. The image is described in terms of nested light and dark regions. This algorithm, successfully implemented in one, two, and three dimensions, can theoretically work with any number of dimensions. The interactive postprocessing developed technique selects regions from the descriptive tree for display in several ways: pointing to a branch of the image description tree, specifying by sliders the range of scale and/or intensity of all regions which should be displayed, and pointing (on the original image) to any pixel in the desired region. The algorithm has been applied to approximately 15 computer tomography (CT) images of the abdomen.
机译:已经开发了一种计算机算法,该算法将灰度图像分割为感兴趣的区域(对象)。这些区域可以为场景分析(包括形状参数计算)或基于表面的阴影图形显示提供基础。该算法通过定义初始图像的连续模糊版本中的像素之间的链接关系来创建用于图像描述的树结构。用嵌套的明暗区域描述图像。该算法成功地在一维,二维和三维中实现,理论上可以在任意数量的维上工作。交互式后处理开发技术以多种方式从描述树中选择要显示的区域:指向图像描述树的一个分支,通过滑块指定应显示的所有区域的比例和/或强度范围,并指向(在原始图像)到所需区域中的任何像素。该算法已应用于腹部的大约15幅计算机断层扫描(CT)图像。

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