Characterization of trabecular bone structure from high-resolution magnetic resonance images using fuzzy logic
Characterization of trabecular bone structure from high-resolution magnetic resonance images using fuzzy logic
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DOI：
10.1016/j.mri.2006.04.010
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发表时间：
2006-10-01
影响因子：
2.5
通讯作者：
Majumdar, Sharmila
中科院分区：
文献类型：
--
作者：
Carballido-Gamio, Julio;Phan, Catherine;Majumdar, Sharmila
本工作的目的是应用模糊逻辑图像处理技术来表征骨小梁结构的高分辨率磁共振图像。在1.5 T和12个在体内的高分辨率磁共振图像的跟骨的绝经后和绝经后妇女的标本的人半径15离体高分辨率磁共振图像。采用模糊聚类对MR数据进行软分割，获得模糊骨体积分数图，然后用三维（3D）模糊几何参数和模糊度进行分析。几何参数包括模糊周长和模糊紧度，模糊度的度量包括模糊度的线性指数、模糊度的二次指数、对数模糊熵和指数模糊熵。模糊参数在1.5 T下使用从微型计算机断层扫描图像计算的3D结构参数进行验证，这允许在1.5 T和3 T下观察真实的骨小梁结构和明显的MR结构指数。采用Pearson相关系数和Bland-Altman方法进行统计学验证。基于Bland-Altman分析，骨体积分数相关值（r）高达0.99（P <0.001），具有良好的一致性，表明模糊聚类是量化该参数的有效技术。基于Bland-Altman分析，furin的测量值也显示与骨小梁数量参数的一致相关性（r > .85; P < .001）和良好的一致性，表明高分辨率磁共振图像中furin的水平可能与骨小梁结构相关。(C)2006爱思唯尔公司All rights reserved.
The purpose of this work was to apply fuzzy logic image processing techniques to characterize the trabecular bone structure with high-resolution magnetic resonance images. Fifteen ex vivo high-resolution magnetic resonance images of specimens of human radii at 1.5 T and 12 in vivo high-resolution magnetic resonance images of the calcanei of peri- and postmenopausal women at 3 T were obtained. Soft segmentation using fuzzy clustering was applied to MR data to obtain fuzzy bone volume fraction maps, which were then analyzed with three-dimensional (3D) fuzzy geometrical parameters and measures of fuzziness. Geometrical parameters included fuzzy perimeter and fuzzy compactness, while measures of fuzziness included linear index of fuzziness, quadratic index of fuzziness, logarithmic fuzzy entropy, and exponential fuzzy entropy. Fuzzy parameters were validated at 1.5 T with 3D structural parameters computed from microcomputed tomography images, which allow the observation of true trabecular bone structure and with apparent MR structural indexes at 1.5 T and 3 T. The validation was statistically performed with the Pearson correlation coefficient as well as with the Bland-Altman method. Bone volume fraction correlation values (r) were up to .99 (P < .001) with good agreements based on Bland-Altman analysis showing that fuzzy clustering is a valid technique to quantify this parameter. Measures of fuzziness also showed consistent correlations to trabecular number parameters (r > .85; P < .001) and good agreements based on Bland-Altman analysis, suggesting that the level of fuzziness in high-resolution magnetic resonance images could be related to the trabecular bone structure. (C) 2006 Elsevier Inc. All rights reserved.