Lehmann T M, Bredno J, Spitzer K
Institute of Medical Informatics, Aachen University of Technology, Aachen, Germany.
Methods Inf Med. 2003;42(1):89-98.
To provide a comprehensive bottom-up categorization of model-based segmentation techniques that allows to select, implement, and apply well-suited active contour models for segmentation of medical images, where major challenges are the high variability in shape and appearance of objects, noise, artifacts, partial occlusions of objects, and the required reliability and correctness of results.
We consider the general purpose of segmentation, the dimension of images, the object representation within the model, image and contour influences, as well as the solution and the parameter selection of the model. Potentials and limits are characterized for all instances in each category providing essential information for the application of active contours to various purposes in medical image processing. Based on prolops surgery planning, we exemplify the use of the scheme to successfully design robust 3D-segmentation.
The construction scheme allows to design robust segmentation methods, which, in particular, should avoid any gaps of dimension. Such gaps result from different image domains and value ranges with respect to the applied model domain and the dimension of relevant subsets for image influences, respectively.
A general segmentation procedure with sufficient robustness for medical applications is still missing. It is shown that in almost every category, novel techniques are available to improve the initial snake model, which was introduced in 1987.
对基于模型的分割技术进行全面的自下而上分类，以便能够选择、实现和应用适合医学图像分割的活动轮廓模型。医学图像分割面临的主要挑战包括物体形状和外观的高度变异性、噪声、伪影、物体的部分遮挡以及结果所需的可靠性和正确性。
我们考虑分割的一般目的、图像维度、模型中的物体表示、图像和轮廓影响，以及模型的解决方案和参数选择。对每个类别中的所有实例进行了优缺点分析，为活动轮廓在医学图像处理中的各种应用提供了基本信息。基于直肠脱垂手术规划，我们举例说明了该方案在成功设计稳健的三维分割中的应用。
构建方案能够设计出稳健的分割方法，特别是应避免任何维度上的差距。这种差距分别源于相对于应用模型域的不同图像域和值范围，以及图像影响相关子集的维度。
仍然缺少一种对医学应用具有足够稳健性的通用分割程序。结果表明，几乎在每个类别中，都有新技术可用于改进1987年引入的初始蛇形模型。
