Browse > Article

A Novel Automatic Algorithm for Selecting a Target Brain using a Simple Structure Analysis in Talairach Coordinate System  

Koo B.B. (Department of Biomedical Engineering, Hanyang University)
Lee Jong-Min (Department of Biomedical Engineering, Hanyang University)
Kim June Sic (Department of Biomedical Engineering, Hanyang University)
Kim In Young (Department of Biomedical Engineering, Hanyang University)
Kim Sun I. (Department of Biomedical Engineering, Hanyang University)
Publication Information
Journal of Biomedical Engineering Research / v.26, no.3, 2005 , pp. 129-132 More about this Journal
Abstract
It is one of the most important issues to determine a target brain image that gives a common coordinate system for a constructing population-based brain atlas. The purpose of this study is to provide a simple and reliable procedure that determines the target brain image among the group based on the inherent structural information of three-dimensional magnetic resonance (MR) images. It uses only 11 lines defined automatically as a feature vector representing structural variations based on the Talairach coordinate system. Average characteristic vector of the group and the difference vectors of each one from the average vector were obtained. Finally, the individual data that had the minimum difference vector was determined as the target. We determined the target brain image by both our algorithm and conventional visual inspection for 20 healthy young volunteers. Eighteen fiducial points were marked independently for each data to evaluate the similarity. Target brain image obtained by our algorithm showed the best result, and the visual inspection determined the second one. We concluded that our method could be used to determine an appropriate target brain image in constructing brain atlases such as disease-specific ones.
Keywords
Target brain image; Common coordinates; Spatial normalization; Brain mapping; Talairach space;
Citations & Related Records
연도 인용수 순위
  • Reference
1 I.D. Dinov, M.S. Mega, P.M. Thompson, L. Lee, R.P. Woods, C.J. Holmes, D.W. Sumners A.W. Toga, 'Analyzing junctional brain images in a probabilistic atlas: a validation of subvolume thresholding', J. Comp. Assist. Tomogr., Vol. 24, pp. 128-138, 2000   DOI   ScienceOn
2 J. Mazziotta, A.W. Toga, A.C. Evans, P. Fox, 'A probabilistic atlas and reference system for the human brain', J. Royal. Soc., pp. 1293-1322, 2001
3 K. Zilles, R. Kawashima, A. Dabringhaus, H. Fukuda, 'Hemispheric shape of European and Japanese brains: 3-D MRI analysis of intersubject variability, ethnical, and gender differences', Neuroimage, Vol. 13, pp. 262-271, 2001   PUBMED
4 U. Yoon, J. Lee, J. Kim, S. Lee, I, Kim, J. S. Kwon, S. I. Kim, 'Modified magnetic resonance image based parcellation method for cerebral cortex using successive fuzzy clustering and boundary detection', Ann. Biomed. Eng., Vol.31, pp. 441-447, 2003   DOI   ScienceOn
5 A.C. Evans, 'Anatomical mapping of functional activation in stereotactic coordinate space', NeuroImage, Vol. 1, pp. 43-53, 1992   DOI   ScienceOn
6 D.L. Collins, 3D Model-based segmentation of individual brain structures from magnetic resonance imaging data, Ph.D. Thesis, McGill Univ., Canada, 1994
7 R.P. Woods, Correlation of brain structure and function, in Brain mapping: The methods, Eds. A.W. Toga and J. Mazziotta: Academic press, pp. 313-42 , 1996
8 P.M. Thompson, R.P. Woods, M.S. Mega, A.W. Toga, 'Mathematical/ computational challenges in creating deformable and probabilistic atlases of the human brain', Human Brain Mapping 9, pp. 81-92, 2000
9 J. Fitzpatrick, J. West, C. Maurer, 'Predicting error in rigid-body point based registration', IEEE Transactions on Medical Imaging, Vol. 17, pp. 694-702, 1998   DOI   ScienceOn
10 A.C. Evans, M. Kamber, D.L. Collins, D. MacDonald, An MRI-based probabilistic atlas of neuroanatomy, In: Magnetic Resonance Scanning and Eplilepsy ed. S. Shorvon: Plenum, New York, pp. 263-274 , 1994
11 S. Umeyama, 'Least squares estimation of transformation parameters between two point patterns', IEEE trans. on Pattern Analysis and Machine Intelligence, Vol. 13, pp. 376-380, 1991   DOI   ScienceOn
12 M.S. Mega, P.M. Thompson, A.W. Toga, 'Sulcal variability in the Alzheimer's brain: correlations with cognition', Neurology 50, pp.145-151, 1998   DOI   ScienceOn
13 J. Kim, J. Lee, Y. Lee, J. Kim, 'Intensity based affine registration including feature similarity for spatial normalization', Computers in Biology and Medicine, Vol. 32, pp. 389-402, 2002   DOI   ScienceOn