Nan-kuei Chen
Nan-kuei Chen is an magnetic resonance imaging (MRI) scientist with extensive expertise in MRI physics, fast MR image acquisition methodology, pulse sequence design, signal processing, and MRI artifact correction. He has developed novel approaches to effectively address various types of challenging MRI artifacts, ranging from echo-planar imaging (EPI) distortions, to susceptibility effect induced signal loss, to EPI Nyquist artifact, to motion-induced phase errors and aliasing artifacts in interleaved EPI based diffusion-weighted imaging. Nan-kuei Chen is the original developer of multiplexed sensitivity encoded (MUSE) MRI, which can measure human brain connectivity in vivo at high spatial-resolution and accuracy. The current focus of his research is the development of innovative data acquisition and reconstruction approaches to enable high-resolution, artifact-free, multi-contrast and quantitative MR imaging for challenging patients within a clinically-feasible time period. Nan-kuei Chen has been serving as PI on NIH-funded R01, R21 and R03 grants, and has had extensive experience as a co-investigator on NIH-funded projects.
Degrees
- PhD Biomedical Engineering
- Northwestern University, Evanston, Illinois, United States
Work Experience
- University of Arizona, Tucson (2016 - Ongoing)
- University of Arizona, Tucson (2016 - Ongoing)
- University of Arizona, Tucson (2016 - Ongoing)
- University of Arizona (2016 - Ongoing)
- Duke University (2016 - 2020)
- Duke University (2007 - 2016)
- Harvard Medical School (2005 - 2007)
Interests
Teaching
Medical Imaging; Magnetic Resonance Imaging
Research
1) Development of high-throughput and motion-immune clinical MRI for imaging challenging patient populations2) Imaging of neuronal connectivity networks for studies of neurological diseases3) High-fidelity and multi-contrast MRI guided intervention4) Characterization and correction of MRI artifacts5) Signal processing and algorithm development6) MRI studies of human development
Courses
Intro to Programming for BME
BME 225 (Fall 2024)
BME 225 (Fall 2023)
BME 225 (Fall 2022)
Honors Independent Study
BME 299H (Spring 2023)
NSCS 399H (Spring 2019)
NSCS 399H (Fall 2018)
Biomedical Imaging
BME 416 (Spring 2019)
BME 516 (Spring 2024)
BME 516 (Spring 2023)
BME 516 (Spring 2022)
Directed Research
BME 492 (Spring 2022)
BME 492 (Fall 2019)
BME 492 (Spring 2019)
BME 492 (Fall 2018)
BME 492 (Spring 2018)
BME 492 (Fall 2017)
Honors Thesis
NSCS 498H (Spring 2020)
NSCS 498H (Fall 2019)
Rsrch Meth Biomed Engr
BME 592 (Fall 2023)
BME 592 (Fall 2021)
BME 592 (Fall 2020)
BME 597G (Fall 2019)
BME 597G (Spring 2018)
BME 597G (Fall 2017)
Independent Study
BME 599 (Spring 2024)
BME 599 (Fall 2023)
BME 599 (Fall 2019)
BME 599 (Spring 2019)
PSY 699 (Fall 2023)
Magnetic Resonance Imaging
BME 639 (Spring 2022)
BME 639 (Spring 2020)
BME 639 (Spring 2018)
Research
BME 900 (Spring 2021)
BME 900 (Fall 2020)
BME 900 (Fall 2019)
Master's Report
BME 909 (Spring 2024)
BME 909 (Fall 2020)
Thesis
BME 910 (Fall 2021)
CMM 910 (Spring 2021)
CMM 910 (Fall 2020)
Dissertation
BME 920 (Fall 2024)
BME 920 (Spring 2024)
BME 920 (Fall 2023)
BME 920 (Spring 2023)
BME 920 (Fall 2022)
BME 920 (Spring 2022)
BME 920 (Fall 2021)
BME 920 (Spring 2021)
BME 920 (Fall 2020)
BME 920 (Spring 2020)
BME 920 (Fall 2019)
BME 920 (Spring 2019)
Selected Publications
Chapters
- Chen, N. (2014). A Unified Machine Learning Method for Task-related and Resting State fMRI data Analysis. In 2014 36th Annual International Conference of the Ieee Engineering in Medicine and Biology Society (Embc).
- Chen, N. (2005). 76-space analysis of grey matter diffusivity: Methods and applications. In Medical Image Computing and Computer-Assisted Intervention - Miccai 2005, Pt 1.
- Chen, N. (2004). MRI intensity nonuniformity correction using simultaneously spatial and gray-level histogram information. In Medical Imaging 2004: Image Processing, Pts 1-3.
Journals/Publications
- Bell, R. P., Meade, C. S., Gadde, S., Towe, S. L., Hall, S. A., & Chen, N. K. (2022). Principal component analysis denoising improves sensitivity of MR diffusion to detect white matter injury in neuroHIV. Journal of neuroimaging : official journal of the American Society of Neuroimaging.
- Chen, N. K., Bell, R. P., & Meade, C. S. (2021). On the down-sampling of diffusion MRI data along the angular dimension. Magnetic resonance imaging, 82, 104-110.
- Haugg, A., Renz, F. M., Nicholson, A. A., Lor, C., Götzendorfer, S. J., Sladky, R., Skouras, S., McDonald, A., Craddock, C., Hellrung, L., Kirschner, M., Herdener, M., Koush, Y., Papoutsi, M., Keynan, J., Hendler, T., Cohen Kadosh, K., Zich, C., Kohl, S. H., , Hallschmid, M., et al. (2021). Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis. NeuroImage, 237, 118207.
- Howard, C. M., Jain, S., Cook, A. D., Packard, L. E., Mullin, H. A., Chen, N. K., Liu, C., Song, A. W., & Madden, D. J. (2022). Cortical iron mediates age-related decline in fluid cognition. Human brain mapping, 43(3), 1047-1060.
- Zhuang, J., Madden, D. J., Cunha, P., Badea, A., Davis, S. W., Potter, G. G., Lad, E. M., Cousins, S. W., Chen, N. K., Allen, K., Maciejewski, A. J., Fernandez, X. D., Diaz, M. T., & Whitson, H. E. (2021). Cerebral white matter connectivity, cognition, and age-related macular degeneration. NeuroImage. Clinical, 30, 102594.
- Haugg, A., Sladky, R., Skouras, S., McDonald, A., Craddock, C., Kirschner, M., Herdener, M., Koush, Y., Papoutsi, M., Keynan, J. N., Hendler, T., Cohen Kadosh, K., Zich, C., MacInnes, J., Adcock, R. A., Dickerson, K., Chen, N. K., Young, K., Bodurka, J., , Yao, S., et al. (2020). Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?. Human brain mapping.
- Kuo, P. H., Zhang, X., Stuehm, C., Chou, Y., & Chen, N. (2020). Functional Magnetic Resonance Imaging Reveals Taiji’s Real-time Effects on Neuronal Networks of the Brain. The Journal of Chinese Health Practices, 1(1).
- Kuo, P. H., Zhang, X., Stuehm, C., Chou, Y., & Chen, N. (2020). Functional Magnetic Resonance Imaging Reveals Taiji’s Real-time Effects on Neuronal Networks of the Brain. The Journal of the International Society of Chinese Health Practices, 1.
- Sui, J., Li, X., Bell, R. P., Towe, S. L., Gadde, S., Chen, N. K., & Meade, C. S. (2020). Structural and functional brain abnormalities in HIV disease revealed by multimodal MRI fusion: association with cognitive function. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.
- Sundman, M. H., Lim, K., Ton That, V., Mizell, J. M., Ugonna, C., Rodriguez, R., Chen, N. K., Fuglevand, A. J., Liu, Y., Wilson, R. C., Fellous, J. M., Rapcsak, S., & Chou, Y. H. (2020). Transcranial magnetic stimulation reveals diminished homoeostatic metaplasticity in cognitively impaired adults. Brain communications, 2(2), fcaa203.
- Zuo, X., Zhuang, J., Chen, N., Cousins, S., Cunha, P., Lad, E. M., Madden, D. J., Potter, G., & Whitson, H. E. (2020). Relationship between neural functional connectivity and memory performance in age-related macular degeneration. Neurobiology of aging, 95, 176-185.
- Chen, N. (2019). Bootstrap analysis of diffusion tensor and mean apparent propagator parameters derived from multiband diffusion MRI. Magnetic Resonance in Medicine.
- Chen, N. (2019). Synergistic effects of marijuana abuse and HIV infection on neural activation during a cognitive interference task. Addiction Biology.
- Chen, N. (2019). The use of Fourier‐domain analyses for unwrapping phase images of low SNR. Magnetic Resonance in Medicine.
- Bell, R. P., Barnes, L. L., Towe, S. L., Chen, N. K., Song, A. W., & Meade, C. S. (2018). Structural connectome differences in HIV infection: brain network segregation associated with nadir CD4 cell count. Journal of neurovirology, 24(4), 454-463.
Proceedings Publications
- Bilgin, A., Do, L., Martin, P. A., Lockhart, E., Bernstein, A. S., Ugonna, C., Dieckhaus, L., Comrie, C., Hutchinson, E. B., Chen, N., Alexander, G. E., Barnes, C. A., & Trouard, T. P. (2021). Accelerating Diffusion Tensor Imaging of the Rat Brain using Deep Learning. In Annual Meeting of the International Society for Magnetic Resonance in Medicine.
- Weinkauf, C. C., Trouard, T. P., Chou, Y., Chen, N., Guzman Perez-Carrillo, G., Ryan, T. L., Altbach, M. I., Johnson, K., Bruck, D., Ugonna, C., McKinnon, A., Bernstein, A. S., & Lindley, M. (2019, Spring). Functional and Microstructural Changes in the Brain After Carotid Endarterectomy. In International Society for Magnetic Resonance in Medicine.
- Bernstein, A., Chen, N., & Trouard, T. P. (2018, June). A Bootstrap Analysis of Diffusion MRI Parameters Derived from Simultaneous Multislice Diffusion MRI. In Joint International Society for Magnetic Resonance in Medicine & The European Society for Magnetic Resonance in Medicine and Biology (ISMRM-ESMRMB) Annual Meeting.
- Chen, N., Chen, N., Chang, H. C., Chang, H. C., Bilgin, A., Bilgin, A., Bernstein, A., Bernstein, A., Trouard, T. P., Trouard, T. P., Chen, N., Chang, H. C., Bilgin, A., Bernstein, A., & Trouard, T. P. (2018, June). A diffusion-matched principal component analysis (DM-PCA) based denoising procedure for high-resolution diffusion-weighted MRI. In Joint International Society for Magnetic Resonance in Medicine & The European Society for Magnetic Resonance in Medicine and Biology (ISMRM-ESMRMB) Annual Meeting.
- Lindley, M., Bernstein, A., Ugonna, C., Bruck, D., Johnson, K., Altbach, M. I., Ryan, L., Chen, N., Chou, Y., Guzman Perez-Carrillo, G., Trouard, T. P., & Weinkauf, C. C. (2018, June). Impact of Carotid Endarterectomy on Functional Connectivity. In Joint International Society for Magnetic Resonance in Medicine & The European Society for Magnetic Resonance in Medicine and Biology (ISMRM-ESMRMB) Annual Meeting, 5562.
Poster Presentations
- Fisher, J. M., Rubio, A., Dolby, A., Ugonna, C. P., Bedrick, E. J., & Chen, N. (2023, May). Threshold-Free Identification of Group-Difference Networks in Neural Connectivity Data. Statistical Methods in Imaging. Minneapolis, Minnesota: Statistics in Imaging Section of the American Statistical Association.
Awards
- Award for Xsede startup research
- Extreme Science and Engineering Discover Environment (XSEDE.org), Fall 2016