Department of Computer Science, School of Engineering, Virginia Commonwealth University, Richmond, USA
Department of Computer Science, School of Engineering, Virginia Commonwealth University, Richmond, USA
Department of Computer Science, School of Engineering, Virginia Commonwealth University, Richmond, USA
Department of Biostatistics, School of Medicine, Virginia Commonwealth University, Richmond, USA
Department of Radiology, School of Medicine, Virginia Commonwealth University, Richmond, USA
Department of Radiology, School of Medicine, Virginia Commonwealth University, Richmond, USA
Department of Emergency Medicine and Michigan Critical Injury and Illness Research Center, University of Michigan, Ann Arbor, USA
Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, USA
Department of Computer Science, School of Engineering, Virginia Commonwealth University, Richmond, USA
Copyright © 2013 Xuguang Qi, Ashwin Belle, Sharad Shandilya, Wenan Chen, Charles Cockrell, Yang Tang, Kevin R. Ward, Rosalyn H. Hargraves, Kayvan Najarian et al. This is
an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any
medium, provided the original work is properly cited.
How to Cite this Article
X. Qi, A. Belle, S. Shandilya, W. Chen, C. Cockrell, Y. Tang, K. Ward, R. Hargraves and K. Najarian, "Ideal Midline Detection Using Automated Processing of Brain CT Image,"
Open Journal of Medical Imaging, Vol. 3 No. 2, 2013, pp. 51-59. doi:
10.4236/ojmi.2013.32007.