• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Biomedical Science and Engineering >Automatic determination of MS lesion subtypes based on fractal analysis in brain MR images
【24h】

Automatic determination of MS lesion subtypes based on fractal analysis in brain MR images

机译：基于分形分析的脑MR图像自动确定MS病变亚型

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper a novel approach based on fractal analysis has been proposed to determine MS lesions into two subtypes (i.e., Enhancing lesions (Acute), T1 “black holes” (chronic) lesions) in Fluid Attenuated Inversion Recovery (FLAIR) MR images, automatically. In the proposed method, firstly, MS lesion voxels are segmented in FLAIR images using Entropy-Based EM Algorithm and Markov Random Field (MRF) model. Then, Fractal dimension of each lesion voxel is computed in FLAIR images and used with signal intensity features (T1-weighted, gadolinium enhanced T1-weighted, T2-weighted). Finally, a neural network classifier is applied to feature vectors. Evaluation of the proposed method was performed by manual segmentation of chronic and acute lesions in gadolinium enhanced T1-weighted (Gad-E-T1-w) images by studying T1-weighted (T1-w) and T2-weighted (T2-w) images, using similarity criteria. The results showed a good correlation between the lesions segmented by the proposed method and by experts manually. Thus, the suggested method is useful to reduce the need for paramagnetic materials in contrast enhanced MR imaging which is a routine procedure for separation of acute and chronic lesions.
机译：在本文中，提出了一种基于分形分析的新颖方法，可将流体衰减反转恢复（FLAIR）MR图像中的MS病变确定为两种亚型（即，增强病变（急性），T1“黑洞”（慢性）病变），自动。在所提出的方法中，首先，使用基于熵的EM算法和马尔可夫随机场（MRF）模型在FLAIR图像中分割MS病变体素。然后，在FLAIR图像中计算每个病变体素的分形维数，并将其与信号强度特征（T1加权，g增强T1加权，T2加权）一起使用。最后，将神经网络分类器应用于特征向量。通过研究T1加权（T1-w）和T2加权（T2-w）对manual增强的T1加权（Gad-E-T1-w）图像中的慢性和急性病变进行手动分割，对提出的方法进行评估图像，使用相似性标准。结果表明，通过所提出的方法和专家手动对病变进行分割之间具有良好的相关性。因此，所建议的方法对于减少对比增强的MR成像中的顺磁性材料是有用的，MR成像是用于分离急性和慢性病变的常规程序。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号