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JP2010000349A Method and system for detecting 3d anatomical object using restricted marginal space learning 有权
标题翻译：使用限制性空间学习检测3D解剖学对象的方法和系统
公开(公告)号：JP2010000349A
公开(公告)日：2010-01-07
申请号：JP2009135170
申请日：2009-06-04
申请人： Siemens Ag , シーメンスアクチエンゲゼルシヤフトSiemens Aktiengesellschaft
发明人： ZHENG YEFENG , GEORGESCU BOGDAN , LING HAIBIN , SCHEUERING MICHAEL , DORIN COMANICIU
IPC分类号： A61B6/03 , G06F17/30 , G06T1/00
CPC分类号： G06K9/3233 , G06K2209/051 , G06T7/75 , G06T2207/10081 , G06T2207/30004
摘要： PROBLEM TO BE SOLVED: To more improve an efficiency for detecting an anatomical object by using an MSL in the detection of the 3D anatomical object.
SOLUTION: As for an inputted medical image, a restricted search range is determined in accordance with a training volume. A position candidate is detected within the restricted search range by using a first classification member to be trained. In the training volume, a direction example is used to form a position-direction assumption from the position candidate. A position-direction candidate is detected from the position-direction assumption by using a second classification member to be trained. In the training volume, a similarity converting assumption is formed from the position-direction candidate in accordance with a scale example. Similarity converting candidates are detected from the similarity converting assumption by using a third classification member to be trained. In accordance with at least one of the similarity converting candidates, the 3D anatomical object is detected in a medical image volume.
COPYRIGHT: (C)2010,JPO&INPIT
摘要翻译：要解决的问题：通过在检测3D解剖体中使用MSL来更有效地提高检测解剖体的效率。
解决方案：对于输入的医学图像，根据训练量确定受限搜索范围。通过使用要训练的第一分类成员在受限搜索范围内检测候选位置。在训练量中，使用方向例来从候选位置形成位置方向假设。通过使用要训练的第二分类成员从位置方向假设检测位置方向候选。在训练量中，根据比例示例从位置方向候补形成相似度转换假设。通过使用要训练的第三分类成员从相似性转换假设检测相似度转换候选。根据相似度转换候选中的至少一个，在医学图像体积中检测3D解剖对象。版权所有（C）2010，JPO＆INPIT

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