发明名称 |
Method and System for Detecting 3D Anatomical Structures Using Constrained Marginal Space Learning |
摘要 |
A method and apparatus for detecting 3D anatomical objects in medical images using constrained marginal space learning (MSL) is disclosed. A constrained search range is determined for an input medical image volume based on training data. A first trained classifier is used to detect position candidates in the constrained search range. Position-orientation hypotheses are generated from the position candidates using orientation examples in the training data. A second trained classifier is used to detect position-orientation candidates from the position-orientation hypotheses. Similarity transformation hypotheses are generated from the position-orientation candidates based on scale examples in the training data. A third trained classifier is used to detect similarity transformation candidates from the similarity transformation hypotheses, and the similarity transformation candidates define the position, translation, and scale of the 3D anatomic object in the medical image volume.
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申请公布号 |
US2009304251(A1) |
申请公布日期 |
2009.12.10 |
申请号 |
US20090471761 |
申请日期 |
2009.05.26 |
申请人 |
SIEMENS CORPORATE RESEARCH, INC.;SIEMENS AKTIENGESELLSCHAFT |
发明人 |
ZHENG YEFENG;GEORGESCU BOGDAN;LING HAIBIN;SCHEUERING MICHAEL;COMANICIU DORIN |
分类号 |
G06K9/00 |
主分类号 |
G06K9/00 |
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