Title: Identification of cortical landmarks based on structural connectivity to subcortical regions

Authors: Degang Zhang; Lei Guo; Xintao Hu; Kaiming Li; Dajiang Zhu; Xi Jiang; Hanbo Chen; Fan Deng; Qun Zhao; Tianming Liu

Addresses: School of Automation, Northwestern Polytechnical University, Xi'an, 710072, China; Department of Physics and Bioimaging Research Center, The University of Georgia, Athens, GA 30605, USA ' School of Automation, Northwestern Polytechnical University, Xi'an, 710072, China ' School of Automation, Northwestern Polytechnical University, Xi'an, 710072, China ' School of Automation, Northwestern Polytechnical University, Xi'an, 710072, China; Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA 30605, USA ' Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, 30605, USA ' Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA 30605, USA ' Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA 30605, USA ' Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA 30605, USA ' Department of Physics and Bioimaging Research Center, The University of Georgia, Athens, GA 30605, USA ' Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA 30605, USA

Abstract: Quantitative assessment of structural connectivities between cortical and subcortical regions has been of increasing interest in recent years. This paper proposes an algorithmic pipeline for identification of reliable cortical landmarks based on the consistent structural connectivity patterns between cortical and subcortical regions. Our experimental results of eight healthy subjects show that reliable and meaningful cortical landmarks can be extracted by using our approaches. Furthermore, subcortical regions can serve as reliable reference points for the identification of consistent corresponding cortical regions across individuals.

Keywords: cortical surface parcellation; subcortical regions; connectivity patterns; cortical landmarks; structural connectivities.

DOI: 10.1504/IJCBDD.2011.044398

International Journal of Computational Biology and Drug Design, 2011 Vol.4 No.4, pp.345 - 360

Received: 28 Aug 2011
Accepted: 17 Oct 2011

Published online: 24 Jan 2015 *

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