中国医疗设备2016，Vol.31Issue(10)：25-28,4.DOI:10.3969/j.issn.1674-1633.2016.10.008
基于质子密度和弛豫时间的大脑MR图像分割新算法
A Novel Approach for Brain MR Image Segmentation Based on Proton Density and Relaxation Time
周啸虎 1高伟 1张子齐1
作者信息
- 1. 南京医科大学附属南京医院 南京市第一医院 放射科，江苏南京 210006
- 折叠
摘要
Abstract
Objective This paper proposed a brain joint segmentation and classiifcation algorithm based on proton density (ρ) and relaxation time (T1) and (T2), instead of the acquired gray level image. Methods Estimation of proton density and relaxation time was made, then the approach exploited the statistical distribution of the involved signals in the complex domain; at last a novel method for identifying the optimal decision regions was proposed, which could achieve the ideal segmentation results.Results Both simulated and real datasets were evaluated by using different methods. Qualitative analysis showed that edges were well retrieved and small structures were preserved and completely clear. Quantitative evaluation results showed that the proposed segmentation algorithm in this paper could provide the best detection probability and false alarm probability. And it could acquire the maximal Dice coefifcient and Jaccard similarity indexes in case of different SNR (15~30 dB).Conclusion The proposed method based onρ,T1 andT2 maps was a feasible segmentation algorithm. And it could provide better robustness in the noise environment, intensity inhomogeneity and clinical applications, which was of great value in clinical popularization.关键词
质子密度/弛豫时间/概率分布/空间关联准则/MR图像分割Key words
proton density/relaxation time/statistical distribution/spatial correlation/MR image segmentation分类
医药卫生引用本文复制引用
周啸虎,高伟,张子齐..基于质子密度和弛豫时间的大脑MR图像分割新算法[J].中国医疗设备,2016,31(10):25-28,4.
