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Multi-step process in computer assisted diagnosis of posterior cruciate ligaments

机译:计算机辅助诊断后交叉韧带的多步骤过程

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摘要

A multi-step methodology resulting in a three-dimensional visualization and construction of feature vector of posterior cruciate ligament is presented. In the first step the location of the posterior cruciate ligament is established using the fuzzy image concept. The fuzzy image concept is based on the entropy measure of fuzziness extended to two dimensions. In order to reduce the area of analysis, the region of interest including the ligament structures is detected. In this case, the fuzzy C-means algorithm with median modification helping to reduce blurred edges was implemented. After finding the region of interest, the fuzzy connectedness procedure was performed. This procedure permitted to extract the ligament structures. On the basis of the extracted posterior cruciate ligament structures, the three-dimensional visualization of this ligament was built and, with the support of experts' knowledge, an appropriate feature vector was constructed and its values assigned for normal and pathological cases. Correct results were obtained for over 88% of 97 cases. (C) 2016 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier Sp. z o.o. All rights reserved.
机译:提出了一种多步方法,可实现三维可视化和后十字韧带特征向量的构建。第一步,使用模糊图像概念确定后十字韧带的位置。模糊图像概念基于扩展到二维的模糊性的熵度量。为了减小分析面积,检测包括韧带结构的感兴趣区域。在这种情况下,实施了具有中间值修改的模糊C均值算法,有助于减少模糊边缘。找到感兴趣的区域后,执行模糊连接过程。该程序允许提取韧带结构。基于提取的后交叉韧带结构,对该韧带进行三维可视化,并在专家的知识支持下,构建适当的特征向量,并将其值分配给正常和病理情况。 97例病例中有88%以上获得了正确的结果。 (C)2016年波兰科学院纳勒奇生物cybernetics和生物医学工程研究所。由Elsevier Sp。发行。动物园。版权所有。

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