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A review of algorithms for medical image segmentation and their applications to the female pelvic cavity

机译:医学图像分割算法及其在女性骨盆腔中的应用综述

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This paper aims to make a review on the current segmentation algorithms used for medical images. Algorithms are classified according to their principal methodologies, namely the ones based on thresholds, the ones based on clustering techniques and the ones based on deformable models. The last type is focused on due to the intensive investigations into the deformable models that have been done in the last few decades. Typical algorithms of each type are discussed and the main ideas, application fields, advantages and disadvantages of each type are summarised. Experiments that apply these algorithms to segment the organs and tissues of the female pelvic cavity are presented to further illustrate their distinct characteristics. In the end, the main guidelines that should be considered for designing the segmentation algorithms of the pelvic cavity are proposed.
机译:本文旨在对当前用于医学图像的分割算法进行综述。算法根据其主要方法进行分类,即基于阈值的算法,基于聚类技术的算法和基于可变形模型的算法。由于最近几十年来对可变形模型进行了深入的研究,因此最后一种类型被关注。讨论了每种类型的典型算法,并总结了每种类型的主要思想,应用领域,优缺点。提出了应用这些算法来分割女性骨盆腔的器官和组织的实验,以进一步说明它们的独特特征。最后,提出了设计骨盆腔分割算法时应考虑的主要指导原则。

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