基于活动轮廓模型的微血管HVEM图像轮廓提取

M. Xiao, Y.Q. Shi, D. Kristol, L. Horn, P. Englet
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引用次数: 6

摘要

报道了高压电子显微镜(HVEM)小血管粗截面蒙太奇图像轮廓提取的研究结果。以前的工作是基于传统的边缘检测操作结合边缘连接,已被证明不足以描述微血管的内部结构室。在这里,一个活动轮廓模型(通常被称为“蛇”)已经被应用于推进以前的工作。活动轮廓模型已被证明是一种强大而灵活的图像理解范式,特别是在医学图像的轮廓提取中。利用所建立的能量函数,通过能量函数的最小化,使活动轮廓在内力(描述轮廓的某些弹性特性)、像力和外力的作用下向边缘吸引。在此主动模型的基础上,首次实现了一种有效的算法,为二维轮廓提取提供了有力的工具。这样得到的结果是令人鼓舞的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contour extraction from HVEM image of microvessel using active contour models
Reports research results on contour extraction from high voltage electron microscope (HVEM) images of thick cross section montages of small blood vessels. The previous work on this subject which was based on the conventional edge detection operations combined with edge linking, has proven inadequate to describe the inner structural compartments of microvessels. Here an active contour model (commonly referred to as "Snakes") has been applied to advance the previous work. Active contour models have proven themselves to be a powerful and flexible paradigm for many problems in image understanding, especially in contour extraction from medical images. With the developed energy functions, the active contour is attracted towards the edges under the action of internal forces (describing some elasticity properties of the contour), image forces and external forces by means of minimization of the energy functions. Based on this active model, an effective algorithm is implemented as a powerful tool for 2D contour extraction in the authors' problem for the first time. The results thus obtained turn out to be encouraging.<>
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