Dyslexia Diagnostics by 3-D Shape Analysis of the Corpus Callosum

被引:14
作者
Elnakib, Ahmed [1 ]
Casanova, Manuel F. [2 ]
Gimel'farb, Georgy [3 ]
Switala, Andrew E. [2 ]
El-Baz, Ayman [1 ]
机构
[1] Univ Louisville, BioImaging Lab, Dept Bioengn, Louisville, KY 40292 USA
[2] Univ Louisville, Dept Psychiat & Behav Sci, Louisville, KY 40292 USA
[3] Univ Auckland, Dept Comp Sci, Auckland 1142, New Zealand
来源
IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE | 2012年 / 16卷 / 04期
关键词
Corpus callosum; diagnosis; dyslexia; modeling; shape analysis; SKELETONIZATION; MINIMUM;
D O I
10.1109/TITB.2012.2187302
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Dyslexia severely impairs learning abilities; therefore, improved diagnostic methods are needed. Neuropathological studies have revealed an abnormal anatomy of the corpus callosum (CC) in dyslexic brains. We propose a new approach for the quantitative analysis of 3-D magnetic resonance images (MRI) of the brain that ensures a more accurate quantification of anatomical differences between the CC of dyslexic and control subjects. The proposed approach consists of three main processing steps: 1) segmenting the CC from a given 3-DMRI using the learned CC shape and visual appearance; 2) extracting the centerline of the CC; and 3) cylindrical mapping of the CC surface for its comparative analysis. Validation on 3-D simulated phantoms demonstrates the ability of the proposed approach to accurately detect the shape variability between two 3-D surfaces. Experimental results revealed significant differences (at the 95% confidence level) between 14 normal and 16 dyslexic subjects in all four anatomical divisions, i.e., splenium, rostrum, genu, and body of their CCs. Moreover, the initial classification results based on the centerline length and CC thickness suggest that the proposed shape analysis is a promising supplement to the current techniques for diagnosing dyslexia.
引用
收藏
页码:700 / 708
页数:9
相关论文
共 35 条
[1]   A FAST LEVEL SET METHOD FOR PROPAGATING INTERFACES [J].
ADALSTEINSSON, D ;
SETHIAN, JA .
JOURNAL OF COMPUTATIONAL PHYSICS, 1995, 118 (02) :269-277
[2]  
[Anonymous], 1977, Lecture notes in Mathematics
[3]  
[Anonymous], P IEEE INT C IM PROC
[4]   Computing and simplifying 2D and 3D continuous skeletons [J].
Attali, D ;
Montanvert, A .
COMPUTER VISION AND IMAGE UNDERSTANDING, 1997, 67 (03) :261-273
[5]   Shape matching and object recognition using shape contexts [J].
Belongie, S ;
Malik, J ;
Puzicha, J .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (04) :509-522
[6]  
Bouix S, 2003, PROC CVPR IEEE, P449
[7]   Reduced brain size and gyrification in the brains of dyslexic patients [J].
Casanova, MF ;
Araque, J ;
Giedd, J ;
Rumsey, JM .
JOURNAL OF CHILD NEUROLOGY, 2004, 19 (04) :275-281
[8]   Minicolumnar pathology in dyslexia [J].
Casanova, MF ;
Buxhoeveden, DP ;
Cohen, M ;
Switala, AE ;
Roy, EL .
ANNALS OF NEUROLOGY, 2002, 52 (01) :108-110
[9]   Global minimum for active contour models: A minimal path approach [J].
Cohen, LD ;
Kimmel, R .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 1997, 24 (01) :57-78
[10]  
El-Baz Ayman., 2008, Computer Vision and Pattern Recognition, P1