医学图像分割技术中变形模型方法的研究综述

Review of Deformable Models in Medical Image Segmentation Techniques

医学图像分割是医学图像处理中的一个经典难题。医学图像分割技术的发展不仅影响到医学图像处理中其他相关技术的发展,如可视化、三维重建等,而且在生物医学图像的分析中也占有极其重要的地位。近年来,由于一些新兴学科在医学图像处理中的应用,医学图像分割技术取得了显著的进展。对近年来兴起的基于变形模型的医学图像分割技术进行研究,综述了其发展历程和基本原理,分析和比较了基于变形模型的图像分割的各种技术的优缺点,展望了该技术领域以后一段时间内的发展趋势。

Medical image segmentation is a classical difficult problem in medical image process. The development of medical image segmentation techniques not only influence on other techniques in image segmentation such as medical image visualization and 3D reconstruction etc, but also play an important role in the analysis of biology medical image analysis. In recent years, owning to some applications of new subjects in medical image process, the medical image segmentation techniques has a remarkable progress. Image segmentation using deformable models encompasses a class of techniques developed in recent years and has been studied extensively. This paper introduces briefly the fundamental principle and theory of image segmentation techniques, analyses and compares the advantages and disadvantages of image segmentation using deformable models and gives the trend of this technique.