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Surface Function Actives

机译：表面功能活性物质

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Deformable models have been widely used in image segmentation since the introduction of the snakes. Later the introduction of level set frameworks to solve the energy minimization problem associated with the deformable model overcame some limitations of the parametric active contours with respect to topo-logical changes by embedding surface representations into higher dimensional functions. However, this may also bring in more computational load so that recent advances in spatio-temporal resolutions of 3D/4D imaging raised some challenges for real-time segmentation, especially for interventional imaging. In this context, a novel segmentation framework. Surface Function Actives (SFA), is proposed for real-time segmentation purpose. SFA has great advantages in terms of potential efficiency, based on its dimensionality reduction for the surface representation. Utilizing implicit representations with variational framework also provides flexibility and benefits currently shared by level set frameworks. An application for minimally-invasive intervention is shown to illustrate the potential applications of this framework.
机译：自从引入蛇以来，可变形模型已广泛用于图像分割。后来引入水平集框架来解决与可变形模型相关的能量最小化问题，通过将表面表示嵌入到高维函数中，克服了拓扑拓扑变化对参数活动轮廓的某些限制。但是，这也可能带来更多的计算负荷，因此3D / 4D成像的时空分辨率方面的最新进展为实时分割（尤其是介入成像）提出了一些挑战。在这种情况下，一个新颖的细分框架。提出了表面功能活性物质（SFA），用于实时分割。 SFA基于减少表面表示的尺寸而在潜在效率方面具有巨大优势。将隐式表示与可变框架一起使用，还可以提供级别集框架当前共享的灵活性和好处。显示了一种用于微创干预的应用程序，以说明此框架的潜在应用程序。

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