In a wide variety of fields, analysis of images involves defining a region and measuring its inherent properties. Such measurements include a region's surface area, curvature, volume, average gray and/or color scale, and so on. Furthermore, the subsequent subdivision of these regions is sometimes performed. These subdivisions are then used to measure local information, at even finer scales. However, simple griding or manual editing methods are typically used to subdivide a region into smaller units. The resulting subdivisions can therefore either not relate well to the actual shape or property of the region being studied (i.e., gridding methods), or be time consuming and based on user subjectivity (i.e., manual methods). The method discussed in this work extracts subdivisional units based on a region's general shape information. We present the results of applying our method to the medical image analysis of nested regions-of-interest of myocardial wall, where the subdivisions are used to study temporal and/or spatial heterogeneity of myocardial perfusion. This method is of particular interest for creating subdivision regions-of-interest (SROIs) when no variable intensity or other criteria within a region need be used to separate a particular region into subunits.
翻译:在一系列广泛的领域,图像分析涉及对一个区域进行定义和测量其固有特性,这种测量包括一个区域的表面面积、曲线、体积、平均灰度和/或颜色尺度,等等。此外,有时会对这些区域进行随后的细分。然后这些细分被用来测量地方信息,甚至更细的尺度。然而,通常使用简单的网格或手工编辑方法将一个区域细分成较小的单位。因此,由此形成的子部分可能与正在研究的区域的实际形状或属性(即网格方法)不完全相关,或者可以消耗时间,并以用户主观性(即人工方法)为基础。本工作讨论的方法根据一个区域的一般形状信息提取子部门单位。我们介绍了将我们的方法应用于对嵌巢区域进行医学图像分析的结果,以图示心心血管壁的利益,在这些区域中,小部分用于研究心肌融合的时间和/或空间差异特性(即网格方法),或者根据用户主观性(即人工方法)进行时间消耗,或者根据用户主观性(即人工方法)进行。本工作讨论的方法根据一个区域的一般形状信息提取子单元,然后根据一个区域的一般形状资料,用我们的方法用于对一个不同的区域进行医学分析。当使用一个特定的密度标准时,这种方法在不同的区域内使用一个特定的强度标准时,这个区域是特别的兴趣。