Publications

Papers:

  • M. Y. Wang, and C. E. Zwilling, “Multivariate computing and robust estimating for outlier and novelty in data and imaging sciences”, Advances in Bioengineering, pp. 317-336, 2015.
  • J. Xia, and M. Y. Wang, “Particle filtering with sequential parameter learning for nonlinear BOLD fMRI signals,” Advances and Applications in Statistics,40(1): 61-74, 2014.
  • C. E. Zwilling, and M. Y. Wang, “Multivariate voronoi outlier detection for time series,” IEEE Healthcare Innovation and Point‐of‐Care Technologies Conf., pp. 300-303, 2014.
  • C. Zhou, C. E. Zwilling, V. D. Calhoun, M. Y. Wang, “Efficient blockwise permutation tests preserving exchangeability,” International Journal of Statistics in Medical Research, 3(2): 145-152, 2014.
  • M. Y. Wang, “Multi-scale information, network, causality, and dynamics: mathematical computation and Bayesian inference to cognitive neuroscience and aging,” Functional Brain Mapping and the Endeavor to Understand the Working Brain, F. Signorelli and D. Chirchiglia, eds., pp. 181-208, 2013.
  • L. T. K. Vo, D. B. Walther, A. F. Kramer, K. I. Erickson, W. R. Boot, M. W. Voss, R. S. Prakash, H. Lee, M. Fabiani, G. Gratton, D. J. Simons, B. P. Sutton, and M. Y. Wang, “Predicting individuals’ learning success from patterns of pre-learning MRI,” PLoS ONE, 6(1): 1-9, 2011.
  • M. Y. Wang, C. Zhou, and J. Xia, “Statistical analysis for recovery of structure and function from brain images,” Biomedical Engineering, Trends, Researches and Technologies, M. A. Komorowska and S. Olsztynska-Janus, eds., pp. 169-190, 2011.
  • U. Sakoglu, G. D. Pearlson, K. A. Keihl, Y. M. Wang, A. M. Michael, and V. D. Calhoun, “A method for evaluating dynamic functional network connectivity and task-modulation: Application to schizophrenia,” Magnetic Resonance Materials in Physics, Biology, and Medicine, 23: 351-366, 2010.
  • C. Zhou, H. Wang, and Y. M. Wang, “Efficient moments-based permutation tests,” Advances in Neural Information Processing Systems (NIPS), 22: 2277-2285, 2009.
  • Y. M. Wang and J. Xia, “Unified framework for robust estimation of brain networks from fMRI using temporal and spatial correlation analyses,” IEEE Trans. on Medical Imaging (TMI), 28(8): 1296-1307, 2009.
  • J. Xia, F. Liang, and Y. M. Wang, “FMRI analysis through Bayesian variable selection with a spatial prior,” IEEE Int. Symp. on Biomedical Imaging (ISBI), pp. 714-717, 2009.
  • C. Zhou and Y. M. Wang, “Hybrid permutation test with application to surface shape analysis,” Statistica Sinica, 18(4): 1553-1568, 2008.
  • J. Xia, F. Liang, and Y. M. Wang, “On clustering fMRI using potts and mixture regression models,” IEEE Engineering in Medicine and Biology Society, pp. 4795-4798, 2009.
  • C. Zhou, Y. Hu, Y. Fu, H. Wang, T. S. Huang, and Y. M. Wang, “3D face analysis for distinct features using statistical randomization,” Acoustics, Speech, and Signal Processing(ICASSP), IEEE Signal Processing Society Press, pp. 981-984, 2008.
  • L. H. Staib, Y. M. Wang, X. Zeng, and J. S. Duncan, “Shape information in deformable models,” Handbook of Medical Image Processing and Analysis, Second Edition, I. Bankman, ed., Elsevier, pp. 167-180, 2008.
  • C. Zhou and Y. M. Wang, “An efficient permutation approach for classical and bioequivalence hypothesis testing of biomedical shape study,” Biomedical Engineering and Informatics, IEEE Press, pp. 737-741, 2008.
  • Y. M. Wang and J. Xia, “Functional interactivity in fMRI using multiple seeds’ correlation analyses – novel methods and comparisons,” Information Processing in Medical Imaging(IPMI), LNCS, 4584: 147-159, 2007.
  • C. Zhou, D. C. Park, M. Styner and Y. M. Wang, “ROI constrained statistical surface morphometry,” IEEE Int. Symp. on Biomedical Imaging(ISBI), pp. 1212-1215, Washington D.C., USA, April 2007.
  • Y. M. Wang, J. Xia and J. Marden, “Multiple correlation and multi-seed for robust inference of functional connectivity in fMRI,” IEEE Int. Symp. on Biomedical Imaging(ISBI), pp. 408-411, 2007.
  • H. Liu, Y. M. Wang and D. G. Simpson, “Bi-criterion clustering and selecting optimal number of clusters via agreement measure,” Joint Statistical Meetings, pp. 2098 – 2105, 2006.
  • Y. M. Wang and C. Zhou, “Integrating and classifying parametric features from fMRI data for brain function characterization,” SPIE Medical Imaging, vol. 6144(6V), pp. 1 – 8, 2006.
  • R. Bansal, L. H. Staib, R. Whitman, Y. M. Wang and B. S. Peterson, “ROC based assessments of 3D cortical surface-matching algorithms,” NeuroImage, vol. 24, no. 1, pp. 150-162, 2005.
  • Y. M. Wang, “Modeling and nonlinear analysis in fMRI via statistical learning,” Advanced Image Processing in Magnetic Resonance Imaging, L. Landini, V. Positano, and M.F. Santarelli, eds., Marcel Dekker International Publisher, pp. 565-586, 2005.
  • L. H. Staib, and Y. M. Wang, “Methods for nonrigid image registration,” Handbook of Geometric Computing: Applications in Pattern Recognition, Computer Vision, Neuralcomputing, and Robotics, E. Bayro-Corrochano, ed., Springer-Verlag, pp. 571-602, 2005.
  • Y. M. Wang and H. Zhang, “Detecting image orientation based on low-level visual content,” Computer Vision and Image Understanding(CVIU), vol. 93, no. 3, pp. 328-346, 2004.
  • Y. M. Wang, J. Zhang, Z. Zhang and B. Guo, “Directional coherence interpolation for three-dimensional grey-level images,” Int. Journal of Image and Graphics, vol. 4, no. 4, pp. 535-561, 2004.
  • Y. M. Wang, R. T. Schultz, R. T. Constable and L. H. Staib, “Nonlinear estimation and modeling of fMRI data using spatio-temporal support vector regression,” Information Processing in Medical Imaging(IPMI), LNCS, 2732: 647-659, 2003.
  • Y. Wang, B. S. Peterson and L. H. Staib, “3D brain surface matching based on geodesics and local geometry,” Computer Vision and Image Understanding(CVIU), vol. 89, no. 2-3, pp. 252-271, 2003.
  • J. Zhang, Y. Wang and B. Guo, “Pyramidal search of maximum coherence direction for biomedical image interpolation,” IEEE Int. Symp. on Biomedical Imaging(ISBI), pp. 887-890, 2002.
  • Y. Wang and H. Zhang, “Content-based image orientation detection with support vector machines,” IEEE Workshop on Content-Based Access of Image and Video Libraries, pp. 17-23, 2001.
  • Y. Wang, Z. Zhang and B. Guo, “3D image interpolation based on directional coherence,” IEEE Workshop on Mathematical Methods in Biomedical Image Analysis(MMBIA), pp. 195-202, 2001.
  • Y. Wang and L. H. Staib, “Physical model-based non-rigid registration incorporating statistical shape information,” Medical Image Analysis(MedIA), vol. 4, no. 1, pp. 7-20, 2000.
  • Y. Wang and L. H. Staib, “Boundary finding with prior shape and smoothness models,” IEEE Trans. on Pattern Analysis and Machine Intelligence(PAMI), vol. 22, no. 7, pp. 738-743, 2000.
  • Y. Wang, B. S. Peterson and L. H. Staib, “Shape-based 3D surface correspondence using geodesics and local geometry,” IEEE Conf. on Computer Vision and Pattern Recognition(CVPR), IEEE Computer Society Press, pp. 644-651 (Vol. II), 2000.
  • Y. Wang and L. H. Staib, “Integrated approaches to non-rigid registration in medical images,” IEEE Workshop on Applications of Computer Vision(WACV), pp. 102-108, 1998.
  • Y. Wang and L. H. Staib, “Elastic model based non-rigid registration incorporating statistical shape information,” Medical Image Computing and Computer-Assisted Intervention(MICCAI), LNCS, 1496: 1162-1173, 1998.
  • Y. Wang and L. H. Staib, “Boundary finding with correspondence using statistical shape models,” IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society Press, pp. 338-345, 1998.

Abstracts:

  • M. Y. Wang, and G. Pellizzer, “Neural representation of uncertainty during planning and decision in primate motor cortex,” Society for Neuroscience (SFN’13), 2013.
  • L. T. K. Vo, D. B. Walther, A. F. Kramer, K. I. Erickson, W. R. Boot, H. Lee, M. W. Voss, R. S. Prakash, M. Fabiani, G. Gratton, and Y. M. Wang, “Predicting training success for a video game,” Human Brain Mapping Conference (HBM’10), Barcelona, Spain, June 2010.
  • C. Zhou, and Y. M. Wang, “General moments-based permutation tests: A framework, method, and application,” Joint Statistical meetings (JSM’09), Washington D.C., USA, August 2009.
  • Y. M. Wang, and J. Xia, “Detecting brain networks based on multiple correlations,” Human Brain Mapping (HBM’07), Chicago, IL, USA, June 2007.
  • C. Zhou, and Y. M. Wang, “Hybrid analysis of brain surface morphometry,” Human Brain Mapping (HBM’07), Chicago, IL, USA, June 2007.

Patent:

  • Y. Wang, and H. Zhang, “Automatic image orientation detection based on classification of low-level image features,” US Patent 6915025, July 5, 2005.

Thesis:

  • Y. Wang, Statistical Shape Analysis for Image Segmentation and Physical Model-Based Non-Rigid Registration, Doctoral dissertation in Electrical Engineering, Yale University, May 1999.