Spline-Based Deforming Ellipsoids for Interactive 3D Bioimage Segmentation
Spline-Based Deforming Ellipsoids for Interactive 3D Bioimage Segmentation
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DOI：
10.1109/tip.2013.2264680
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发表时间：
2013-10-01
影响因子：
10.6
通讯作者：
Unser, Michael
中科院分区：
文献类型：
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作者：
Delgado-Gonzalo, Ricard;Chenouard, Nicolas;Unser, Michael
我们提出了一种新的快速主动轮廓模型（又名蛇），用于 3D 显微镜中的图像分割。我们引入了一种依赖于指数 B 样条基础的参数化设计，使我们能够构建能够再现椭球体的蛇。我们设计的基地具有尽可能短的支撑，但受到一些限制。因此，计算效率最大化。所提出的 3D Snake 可以高精度地近似斑点状物体，并且可以完美地再现球体和椭球体，无论其位置和方向如何。由于我们的能量计算方案中使用了高斯定理，优化过程非常快。我们的技术可以产生成功的分割结果，即使对于对象轮廓未明确定义的具有挑战性的数据也是如此。这是由于我们的参数化方法允许人们优先考虑先前的形状。此外，本文还提供了一种软件，可以通过直观地操作几个控制点来完全控制蛇。
We present a new fast active-contour model (a.k.a. snake) for image segmentation in 3D microscopy. We introduce a parametric design that relies on exponential B-spline bases and allows us to build snakes that are able to reproduce ellipsoids. We design our bases to have the shortest-possible support, subject to some constraints. Thus, computational efficiency is maximized. The proposed 3D snake can approximate blob-like objects with good accuracy and can perfectly reproduce spheres and ellipsoids, irrespective of their position and orientation. The optimization process is remarkably fast due to the use of Gauss' theorem within our energy computation scheme. Our technique yields successful segmentation results, even for challenging data where object contours are not well defined. This is due to our parametric approach that allows one to favor prior shapes. In addition, this paper provides a software that gives full control over the snakes via an intuitive manipulation of few control points.