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Variational approach to semi-automated 2D image segmentation

机译:半自动2D图像分割的变分方法

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The segmentation of 2D biomedical images is very complex problem which has to be solved interactively. Original MRI, CT, PET, or SPECT image can be enhanced using variational smoother. However, there are Regions of Interest (ROI) which can be exactly localized. The question is how to design human interaction with computer for user friendly biomedical service. Our approach is based on user selected points which determine the ROI border line. The relationship between point positions and image intensity is subject of variational interpolation using thin plate spline model. The general principle of segmentation is demonstrated on biomedical images of human brain.
机译:2D生物医学图像的分割是非常复杂的问题,必须以交互方式解决。可以使用变分光滑可以增强原始MRI,CT,PET或SPECT图像。但是,有兴趣区域(ROI)可以完全局限化。问题是如何设计与计算机的人类互动,以便用户友好的生物医学服务。我们的方法是基于用户选择的点,确定ROI边界线。点位置和图像强度之间的关系使用薄板样条模型进行变分插值。对人脑的生物医学图像证明了分割的一般原则。

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