The HaxbyLab@Dartmouth

Yu-Chien Wu

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Yu-Chien Wu

MRI Physicist, Research Assistant Professor

M.D. Kaohsiung Medical University, Kaohsiung, Taiwan

Ph.D. University of Wisconsin – Madison


Address:6207 Moore Hall, Rm420 Hanover, NH03755
Phone:(+1)(603) 646-2909

Research focus

My research focuses on diffusion weighted imaging (DWI) using magnetic resonance imaging (MRI) to study white matter and gray matter structures of the human brain. I am interested in methodology development of DWI techniques including Diffusion Tensor Imaging (DTI), q-space imaging (QSI), Diffusion Spectrum Imaging (DSI) and High Angular Resolution Diffusion Imaging (HARDI). In particular, I have developed the HYbrid Diffusion Imaging (HYDI) that combines different DWI imaging strategies to facilitate DWI studies in the clinical imaging setting. Currently, my projects include: (1) developing a novel MRI pulse sequence for fast and high resolution diffusion imaging, (2) exploring the time dependence of the water probability density function (PDF) using ActiveAx, dPFG or OGSE sequences, (3) using a MultiVariate Pattern Analysis (MVPA) approach on fiber orientation distribution functions (ODF) to classify amygdala subnuclei as well as white matter structures, (4) using HYDI on patients with acute traumatic brain injury and multiple sclerosis, (5) using HARDI to study deep brain stimulation (DBS) on patients with treatment resistant depression (TRD).

Advanced DWI has significant clinical potential, especially in certain neurosurgical procedures (e.g., DBS) where mapping of fine white matter tracts is crucial for optimizing surgical planning. Unfortunately, such advanced approaches often require a significant amount of scan time that is prohibitive for most clinical applications. We have focused on developing a novel imaging technique for DWI that is faster than the single-shot EPI (SS-EPI) sequence commonly used in diffusion imaging. Once developed, such a pulse sequence would allow higher angular resolution diffusion data to be acquired in a short period of time, thereby greatly increasing the clinical potential of advanced diffusion imaging techniques. The time dependence of the water diffusion function could reveal the physical properties on the cellular level, e.g., neuron/axon diameter, density and extra/intra-cellular water compartments. However, these experiments (e.g., ActiveAx, dPFG, and OGSE) have not been applied in clinical researches due to the long scan time. With the new fast sequence for diffusion, I would like to explore and implement these sequences for clinical scanners. My lab has started to work on computational neuroimaging using diffusion-imaging data to reveal fine structures of the brain and white matter connectivity. In particular, we are currently developing an auto-segmentation of amygdalae and white matter using machine learning, e.g., MVPA.

Lab members

Research Specialist: Brian Stirling ( Post-doc: Chandana Kodiweera Nambukara (


Peer-reviewed Publications


[CGG+12]Connolly, A. C. , Guntupalli, J. S. , Gors, J. , Hanke, M. , Halchenko, Y. O., Wu, Y. , Abdi, H. and Haxby, J. V. (2012). Representation of biological classes in the human brain. Journal of Neuroscience, 32, 2608-2618. [PDF] DOI: 10.1523/JNEUROSCI.5547-11.2012, cited by: 234
[HCW+12b]Hosseinbor, A. P., Chung, M. K., Wu, Y. and Alexander, A. L. (2012). Bessel Fourier Orientation Reconstruction (BFOR): An analytical diffusion propagator reconstruction for hybrid diffusion imaging and computation of q-space indices.. Neuroimage, 64, 650-670. [PDF] [URL]
[SAM+12]Samsonov, A., Alexander, A. L., Mossahebi, P., Wu, Y. , Duncan, I. D. and Field, A. S. (2012). Quantitative MR imaging of two-pool magnetization transfer model parameters in myelin mutant shaking pup.. Neuroimage, 62, 1390-8. [PDF] [URL], cited by: 41
[HCW+11]Hosseinbor, A. P., Chung, M. K., Wu, Y. and Alexander, A. L. (2011). Bessel Fourier orientation reconstruction: an analytical EAP reconstruction using multiple shell acquisitions in diffusion MRI.. Med Image Comput Comput Assist Interv, 14, 217-25. [PDF] [URL], cited by: 12
[WFD+11]Wu, Y. , Field, A. S., Duncan, I. D., Samsonov, A. A., Kondo, Y., Tudorascu, D. and Alexander, A. L. (2011). High b-value and diffusion tensor imaging in a canine model of dysmyelination and brain maturation.. Neuroimage, 58, 829-37. [PDF] [URL], cited by: 45
[WFW+11]Wu, Y. , Field, A. S., Whalen, P. J. and Alexander, A. L. (2011). Age- and gender-related changes in the normal human brain using hybrid diffusion imaging (HYDI). Neuroimage, 54, 1840-53. [PDF] DOI: 10.1016/j.neuroimage.2010.09.067, cited by: 44
[OHW+10]O, (2010). Helium-3 MR q-space imaging with radial acquisition and iterative highly constrained back-projection. Magn Reson Med, 63, 41-50. [PDF] DOI: 10.1002/mrm.22158
[LCW+08]Liu, H., Chen, H., Wu, Y. , Lim, S., Huang, C., Hsu, Y., Wai, Y. and Wu, T. (2008). False-positive analysis of functional MRI during simulated deep brain stimulation: a phantom study. J Magn Reson Imaging, 27, 1439-42. [PDF] DOI: 10.1002/jmri.21222
[WFA08]Wu, Y. , Field, A. S. and Alexander, A. L. (2008). Computation of diffusion function measures in q-space using magnetic resonance hybrid diffusion imaging. IEEE Trans Med Imaging, 27, 858-65. [PDF] DOI: 10.1109/TMI.2008.922696, cited by: 20
[WA07a]Wu, Y. and Alexander, A. L. (2007). Hybrid diffusion imaging. Neuroimage, 36, 617-29. [PDF] DOI: 10.1016/j.neuroimage.2007.02.050, cited by: 166
[WA07b]Wu, Y. and Alexander, A. L. (2007). A method for calibrating diffusion gradients in diffusion tensor imaging. J Comput Assist Tomogr, 31, 984-93. [PDF] DOI: 10.1097/rct.0b013e31805152fa
[ALW+06]Alexander, A. L., Lee, J. E., Wu, Y. and Field, A. S. (2006). Comparison of diffusion tensor imaging measurements at 3.0 T versus 1.5 T with and without parallel imaging. Neuroimaging Clin N Am, 16, 299-309. DOI: 10.1016/j.nic.2006.02.006, cited by: 70
[AWV06]Alexander, A. L., Wu, Y. and Venkat, P. C. (2006). Hybrid diffusion imaging (HYDI). Conf Proc IEEE Eng Med Biol Soc, 1, 2245-8. [PDF] DOI: 10.1109/IEMBS.2006.259453
[FWA05]Field, A. S., Wu, Y. and Alexander, A. L. (2005). Principal diffusion direction in peritumoral fiber tracts: Color map patterns and directional statistics. Ann N Y Acad Sci, 1064, 193-201. [PDF] DOI: 10.1196/annals.1340.037
[FAW+04]Field, A. S., Alexander, A. L., Wu, Y. , Hasan, K. M., Witwer, B. and Badie, B. (2004). Diffusion tensor eigenvector directional color imaging patterns in the evaluation of cerebral white matter tracts altered by tumor. J Magn Reson Imaging, 20, 555-62. [PDF] DOI: 10.1002/jmri.20169, cited by: 187
[WFC+04]Wu, Y. , Field, A. S., Chung, M. K., Badie, B. and Alexander, A. L. (2004). Quantitative analysis of diffusion tensor orientation: theoretical framework. Magn Reson Med, 52, 1146-55. [PDF] DOI: 10.1002/mrm.20254

Conference Proceedings

[HCW+12a]Hosseinbor, A. P., Chung, M. K., Wu, Y. , Fleming, J. O., Field, A. S. and Alexander, A. L. (2012). Extracting Quantitative Measures from EAP: A Small Clinical Study Using BFOR.. In Ayache, Nicholas and Delingette, Herv~Acopyright and Golland, Polina and Mori, Kensaku (Eds.) MICCAI (2), : Springer. [PDF] [URL], cited by: 3
[MWA09]Chung, M. K., Wu, Y. and Alexander, A. L. (2009). 3D Eigenfunction Expansion of Sparsely Sampled 2D Cortical Data. In (Eds.) ISBI, : IEEE. [PDF] DOI: 10.1109/ISBI.2009.5192996, cited by: 2


[CWH+11]Connolly, A. C. , Wu, Y. , Halchenko, Y. O. , Guntupalli, J. S. and Haxby, J. V. (2011). Scanning parameters for optimal decoding using a 32-channel head coil for fMRI. Vision Sciences Society Annual Meeting, Naples, FL. Poster. [PNG]

Ph.D. Theses

[W06]Wu, Y. (2006). Diffusion MRI: Tensors and beyond (Doctoral dissertation). `THE UNIVERSITY OF WISCONSIN-MADISON, `.

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