Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, Brazil.
Comput Biol Med. 2012 May;42(5):509-22. doi: 10.1016/j.compbiomed.2012.01.004. Epub 2012 Feb 13.
In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI, and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.
本文针对 3D MR 图像中的“头骨剥离”问题提出了一种新的方法，该方法采用了高效且独特的直方图分析。这种分析的一个基本组成部分是一种根据与高斯拟合的最大偏差位置对直方图进行分区的算法。在我们的实验中，我们使用了一个综合的图像数据库，包括合成和真实的 MRI，并将我们的方法与另外两种著名的方法（BSE 和 BET）进行了比较。对于所有数据集，我们都取得了优异的结果。我们的方法还高度独立于参数调整，并且在相当大的信噪比变化范围内非常稳健。
