Simple paradigm for extra-cerebral tissue removal: Algorithm and analysis

被引:99
作者
Carass, Aaron [1 ]
Cuzzocreo, Jennifer [2 ]
Wheeler, M. Bryan [1 ]
Bazin, Pierre-Louis [2 ]
Resnick, Susan M. [3 ]
Prince, Jerry L. [1 ]
机构
[1] Johns Hopkins Univ, Dept Elect & Comp Engn, Baltimore, MD 21218 USA
[2] Johns Hopkins Univ, Dept Radiol & Radiol Sci, Baltimore, MD 21218 USA
[3] NIA, Lab Personal & Cognit, Baltimore, MD 21224 USA
关键词
Brain extraction; Skull stripping; Watershed principle; Segmentation; Medical image processing; BRAIN SEGMENTATION; CLASSIFICATION; IMAGES; PET;
D O I
10.1016/j.neuroimage.2011.03.045
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Extraction of the brain i.e. cerebrum, cerebellum, and brain stem from T1-weighted structural magnetic resonance images is an important initial step in neuroimage analysis. Although automatic algorithms are available, their inconsistent handling of the cortical mantle often requires manual interaction, thereby reducing their effectiveness. This paper presents a fully automated brain extraction algorithm that incorporates elastic registration, tissue segmentation, and morphological techniques which are combined by a watershed principle, while paying special attention to the preservation of the boundary between the gray matter and the cerebrospinal fluid. The approach was evaluated by comparison to a manual rater, and compared to several other leading algorithms on a publically available data set of brain images using the Dice coefficient and containment index as performance metrics. The qualitative and quantitative impact of this initial step on subsequent cortical surface generation is also presented. Our experiments demonstrate that our approach is quantitatively better than six other leading algorithms (with statistical significance on modern T1-weighted MR data). We also validated the robustness of the algorithm on a very large data set of over one thousand subjects, and showed that it can replace an experienced manual rater as preprocessing for a cortical surface extraction algorithm with statistically insignificant differences in cortical surface position. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:1982 / 1992
页数:11
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