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1. 发明授权

US6021213A Automatic contextual segmentation for imaging bones for osteoporosis therapies 失效
标题翻译：用于骨质疏松治疗的成像骨骼的自动上下文分割
公开(公告)号：US6021213A
公开(公告)日：2000-02-01
申请号：US662391
申请日：1996-06-13
申请人： Jeffrey Donald Helterbrand , Richard Earl Higgs, Jr. , Philip Wayne Iversen
发明人： Jeffrey Donald Helterbrand , Richard Earl Higgs, Jr. , Philip Wayne Iversen
IPC分类号： G06T5/00 , G06K9/00
CPC分类号： G06T7/0081 , G06T7/0091 , G06T2207/10072 , G06T2207/10116 , G06T2207/20141 , G06T2207/30008
摘要： An automatic contextual segmentation method which can be used to identify features in QCT images of femora, tibiae and vertebrae. The principal advantages of this automatic approach over traditional techniques such as histomorphometry are, 1) the algorithms can be implemented in a fast, uniform, non-subjective manner across many images allowing unbiased comparisons of therapeutic efficacy, 2) much larger volumes in the region of interest can be analyzed, and 3) QCT can be used longitudinally. Two automatic contextual segmentation algorithms relate to a cortical bone algorithm (CBA) and a whole bone algorithm (WBA). These methods include a preprocessing step, a threshold selection step, a segmentation step satisfying logical constraints, a pixel wise label image updating step, and a feature extraction step; with the WBA including whole bone segmentation, cortical segmentation, spine segmentation, and centrum segmentation. The algorithms are constructed to provide successful segmentations for known classes of bones with known topological constraints.
摘要翻译：自动上下文分割方法，可用于识别股骨，胫骨和椎骨的QCT图像中的特征。这种自动方法与传统技术（如组织形态计量学）相比的主要优点是：1）可以以快速，均匀，非主观的方式在许多图像上实现算法，从而允许无偏差地比较治疗功效，2）该区域的体积更大可以分析，3）QCT可以纵向使用。两种自动上下文分割算法涉及皮质骨算法（CBA）和全骨算法（WBA）。这些方法包括预处理步骤，阈值选择步骤，满足逻辑约束的分割步骤，像素图标签图像更新步骤和特征提取步骤; WBA包括全骨分割，皮质分割，脊柱分割和中心分割。这些算法被构造成为具有已知拓扑约束的已知类型的骨提供成功的分割。

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