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Method for automatically constructing patient-specific anatomic model based on statistical shape model (SSM)

机译:基于统计形状模型自动构建患者特定解剖模型的方法

摘要

#$%^&*AU2020101643A420200910.pdf#####ABSTRACT The present invention provides a method for automatically constructing a patient-specific anatomic model based on statistical shape model (SSM), which mainly includes four processing phases, namely the phase of splitting of a region of interest, the phase of vertex shrinkage, the phase of response setup, and the phase of generation of the patient-specific anatomic model. According to the invention, firstly, preprocessing of input data and enhancement of a region of interest are carried out, and the region of interest is split from each of CT scan images of specific patients. The split regions of interest are then used as training samples which are subjected to gridding with a triangle, and triangular grids are subjected to iterative shrinkage by a vertex shrinkage strategy. A response is then set up between a template sample and a target sample, and the template sample is aligned to the target sample. Finally, a general expression for anatomic structures of patients is generated. By this method, a patient-specific anatomic model can be effectively constructed to assist medical professionals with quick analysis of a patient's condition, thereby providing a reasonable plan for the patient's follow-up treatment.1 / 6 0CD a SampleD/Generation of Image Image Sample Gera en nhancemenD - Registration _, Image -+Expression of E) Respo ) 0 a-= . nse Alignment -*Anatomic U) Setup FIG. 1 FIG. 2
机译:#$%^&* AU2020101643A420200910.pdf #####抽象本发明提供了一种自动构建患者特异性的方法基于统计形状模型(SSM)的解剖模型,主要包括四个处理阶段,即感兴趣区域的分裂阶段,顶点收缩阶段,反应建立的阶段,以及患者特定解剖模型的生成阶段。根据本发明,首先,对输入数据进行预处理并增强输入区域。进行感兴趣的区域,并从每个特定的CT扫描图像中分离出感兴趣的区域耐心。然后将感兴趣的分割区域用作训练样本,用三角形网格化,并且三角形网格受到顶点的迭代收缩收缩策略。然后在模板样本和目标样本之间建立响应,并且模板样本与目标样本对齐。最后是解剖学的一般表达产生患者的结构。通过这种方法,可以创建患者特定的解剖模型有效地构造为可以帮助医疗专业人员快速分析患者的状况,从而为患者的后续治疗提供合理的计划。1/60CD a> SampleD / Generation of图片图片样品格拉增强功能-注册_,图像-+E)Respo)0 a- =。 nse对齐-*原子的U)设定图。 1个图。 2

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