A robust and accurate algorithm for estimating the complexity of the cortical surface

	A robust and accurate algorithm for estimating the complexity of the cortical surface
	Jiang, Jiefeng 1; Zhu, Wanlin 2; Shi, Feng 1; Zhang, Yuanchao 2; Lin, Lei 2; Jiang, Tianzi1
刊名	JOURNAL OF NEUROSCIENCE METHODS
	2008-07-15
卷号	172 期号:1 页码:122-130
关键词	anatomic MRI box-counting cortical complexity fractal dimension reconstructed cortical surface
英文摘要	A fractal dimension (FD) gives a highly compact description of the shape characteristics of the human brain and has been employed in many studies on brain morphology. The accuracy of FD estimation depends on the precision of the input shape description. Facilitated by automatic cerebral cortical surface reconstruction algorithms, the shape of the cerebral cortex can be more precisely modeled using Magnetic Resonance (MR) imaging. Since the reconstructed cortical surface is represented by triangles, rather than by points, as is typical of models that use voxels, the voxel-based FD estimation algorithms that have been used in previous studies do not work when using the cortical surface as the input. Thus, designing a new algorithm that is able to estimate the FD from a surface representation becomes of particular interest. In this paper, a robust and accurate FD estimation algorithm is proposed. The algorithm is based on a box-triangle intersection checking strategy, which is used for the first time in brain analyses, and a box-counting method, which has been widely used in FD computations of the human brain and other natural objects. These two features endowed the algorithm with robustness. The accuracy of the algorithm was validated via several experiments using both manually generated datasets and real MR images. As a result of these features, the algorithm is also suitable for estimating the FD of fractals in addition to that of the cerebral cortex. (C) 2008 Elsevier B.V. All rights reserved.
WOS标题词	Science & Technology ; Life Sciences & Biomedicine
类目[WOS]	Biochemical Research Methods ; Neurosciences
研究领域[WOS]	Biochemistry & Molecular Biology ; Neurosciences & Neurology
关键词[WOS]	MAGNETIC-RESONANCE IMAGES ; AUTOMATED 3-D EXTRACTION ; FRACTAL DIMENSION ; WHITE-MATTER ; CEREBRAL-CORTEX ; HUMAN BRAIN ; SCHIZOPHRENIA ; RECONSTRUCTION ; GYRIFICATION ; ASYMMETRY
收录类别	SCI
语种	英语
WOS记录号	WOS:000257485800018
公开日期	2015-12-24
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/9570]
专题	自动化研究所_09年以前成果
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 2.Zhejiang Univ, Dept Math, Hangzhou 310027, Peoples R China
推荐引用方式 GB/T 7714	Jiang, Jiefeng,Zhu, Wanlin,Shi, Feng,et al. A robust and accurate algorithm for estimating the complexity of the cortical surface[J]. JOURNAL OF NEUROSCIENCE METHODS,2008,172(1):122-130.
APA	Jiang, Jiefeng,Zhu, Wanlin,Shi, Feng,Zhang, Yuanchao,Lin, Lei,&Jiang, Tianzi.(2008).A robust and accurate algorithm for estimating the complexity of the cortical surface.JOURNAL OF NEUROSCIENCE METHODS,172(1),122-130.
MLA	Jiang, Jiefeng,et al."A robust and accurate algorithm for estimating the complexity of the cortical surface".JOURNAL OF NEUROSCIENCE METHODS 172.1(2008):122-130.