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AUTOMATIC SPATIAL CONTEXT BASED MULTI-OBJECT SEGMENTATION IN 3D IMAGES

机译:基于自动空间上下文的3D图像多对象分割

摘要

Methods and systems for automatic classification of images of internal structures of human and animal bodies. A method includes receiving a magnetic resonance (MR) image testing model and determining a testing volume of the testing model that includes areas of the testing model to be classified as bone or cartilage. The method includes modifying the testing model so that the testing volume corresponds to a mean shape and a shape variation space of an active shape model and producing an initial classification of the testing volume by fitting the testing volume to the mean shape and the shape variation space. The method includes producing a refined classification of the testing volume into bone areas and cartilage areas by refining the boundaries of the testing volume with respect to the active shape model and segmenting the MR image testing model into different areas corresponding to bone areas and cartilage areas.
机译:自动分类人体和动物体内结构图像的方法和系统。一种方法包括接收磁共振(MR)图像测试模型并确定该测试模型的测试体积,该测试体积包括该测试模型的要被分类为骨骼或软骨的区域。该方法包括修改测试模型,使得测试体积对应于活动形状模型的平均形状和形状变化空间,以及通过将测试体积拟合到平均形状和形状变化空间来产生测试体积的初始分类。 。该方法包括通过相对于活动形状模型细化测试体积的边界并且将MR图像测试模型分割成与骨头区域和软骨区域相对应的不同区域,来将测试体积分类为骨区域和软骨区域。

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