Fast robust automated brain extraction
Fast robust automated brain extraction
复制标题
DOI：
10.1002/hbm.10062
复制
发表时间：
2002-11-01
影响因子：
4.8
通讯作者：
Smith, SM
中科院分区：
文献类型：
--
作者：
Smith, SM
一种将头部磁共振图像分割为脑区和非脑区的自动化方法已经被开发出来。它非常稳健和准确，并且已经在来自各种各样扫描仪以及采用各种各样磁共振序列获取的数千个数据集上进行了测试。这种方法，即脑提取工具（BET），使用一种可变形模型，通过应用一组局部自适应的模型力使其演变以适应大脑表面。该方法速度非常快，在应用之前不需要预配准或其他预处理。我们描述了这种新方法，并给出了结果示例以及针对“金标准”手工分割和另外两种流行的自动化方法进行大量定量测试的结果。（C）2002威利 - 利斯公司
An automated method for segmenting magnetic resonance head images into brain and nonbrain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods. (C) 2002 Wiley-Liss, Inc.