Xiaofu
He, Ph.D. Associate
Professor Department
of Psychiatry, Columbia University 1051
Riverside Drive, Unit43 New
York, NY 10032 Tel.
646-774-5875 Email:
[email protected] Affiliation:
https://datascience.columbia.edu/people
EXPERTISE
˛ Brain Imaging including DTI
and fMRI
˛ Decoded neurofeedback (DecNef)
˛ Real-time fMRI/EEG
neurofeedback
˛ Image Processing and
Computer vision
˛ Machine learning
and Computational Modeling
˛ Pattern Recognition and Biometrics
˛ Software Engineering
RESEARCH PROFILE
Dr. Xiaofu He is an Associate Professor of Clinical
Neurobiology in the Department of Psychiatry at Columbia University Irving
Medical Center (CUIMC) and a Research Scientist at the New York State
Psychiatric Institute (NYSPI). His interdisciplinary research integrates
computer science, machine learning, multimodal neuroimaging, and neurobiology
to advance the understanding, diagnosis, and treatment of psychiatric
disorders. His research focuses on developing and applying advanced brain
imaging and AI/deep learning methods to identify biomarkers of psychiatric
disorders, improve diagnostic and predictive models, and develop personalized
interventions. His work encompasses four major areas: (1) advancing diffusion
tensor imaging (DTI) preprocessing and automated quality control methods; (2)
identifying neuroimaging-based biomarkers of mental disorders; (3) developing
AI and deep learning approaches for psychiatric diagnosis and personalized
treatment; and (4) investigating real-time fMRI, EEG, and fNIRS
neurofeedback as novel approaches to psychiatric treatment. Across these areas,
his research aims to translate advances in computational methods and
neuroimaging into more precise and effective approaches to psychiatric
diagnosis and treatment.
EDUCATION / TRAINING
2014 Postdoctoral training Columbia University
2011 Postdoctoral training Georgia
Health Sciences University
2007 Ph.D. in Pattern Recognition
and Intelligent Systems Shanghai Jiao Tong University
PROFESSIONAL EXPERIENCE
2026 – Present Associate Professor, Department of
Psychiatry, Columbia University, New York, NY
2026 – Present Adjunct Associate Professor, Department of
Statistics, Columbia University, New York, NY
2018 – Present Affiliated faculty member, Data Science
Institute, Columbia University, New York, NY
2014 – Present Research Scientist, Research Foundation for
Mental Hygiene, Inc., New York State Psychiatric Institute, New York, NY
2018 – 2026 Adjunct Assistant Professor, Department
of Statistics, Columbia University, New York, NY
2014 – 2026 Assistant Professor, Department of
Psychiatry, Columbia University, New York, NY
2011 – 2014 Postdoctoral Research Scientist, Brain
Imaging Lab, Department of Psychiatry, Columbia University, New York, NY
2009 – 2011 Postdoctoral Research Fellow, Brain
& Behavior Discovery Institute, Georgia Health Sciences University,
Augusta, GA
2007 – 2009 Assistant Professor, Department of Computer
Science and Technology, East China Normal University, Shanghai, China
SELECTED HONORS / AWARDS
2015 Columbia Irving
Institute Imaging Pilot Award, New York, NY
2014 New York
State Psychiatry Institute MRI Pilot Award, New York, NY
2013 NARSAD Young
Investigator Award, New York, NY
2010 Travel Award
for Oral Presentation, Joint South East Nerve Net and
Georgia/South Carolina, Neuroscience Consortium Conference, Atlanta, GA
SELECTED
PUBLICATIONS/PRESENTATIONS
2026
Six H, Oka T, Valevicius D, Göktepe-Kavis P, He X, Taschereau-Dumouchel V,
Cortese A, The DecNef toolbox: An enhanced toolkit
for fMRI-based decoded neurofeedback, Real-Time Functional Imaging and
Neurofeedback conference (rtFIN 2026), October 4-7,
2026, Geneva, Switzerland. Poster.
He X, Welch
EE, Tambini A, Xu Y, Xu M, Davachi L, Real-Time fMRI
Neurofeedback Targeting Hippocampal–Cortical Connectivity to Enhance Memory
Consolidation, Real-Time Functional Imaging and Neurofeedback conference (rtFIN 2026), October 4-7, 2026, Geneva, Switzerland. Poster.
2025
He X, Wang
Y, Gao Y, Wang X, Sun Z, Zhu H, Leong K, Xu B (2025), CalciumZero:
a toolbox for fluorescence calcium imaging on iPSC derived brain organoids, Brain
Informatics, (2025) 12:2. https://doi.org/10.1186/s40708-024-00248-5.
He X, Luo Y, Li R, Tong H, Thorp J, Spagna A, He X,
A Deep-Learning Based Decoded EEG Neurofeedback Platform Using Muse-S,
International Symposium on Decoded Neurofeedback, July 17-18, 2025, Nara,
Japan. Poster
2024
Zheng X, Ravid O, Barry R.A.J, Kim Y, Wang Q, Kim Y,
Zhu X, He X (2024), Denoising Variational Autoencoder as a Feature
Reduction Pipeline for the diagnosis of Autism based on Resting-state fMRI, arXiv preprint arXiv:2410.00068. 2024 September. https://doi.org/10.48550/arXiv.2410.00068.
Huggins AA, Baird CL, Briggs M, Laskowitz S, Hussain
A, Fouda S, Haswell C, Sun D, Salminen LE, Jahanshad N, Thomopoulos SI, Veltman
DJ, Frijling JL, Olff M, van Zuiden M, Koch SBJ, Nawjin L, Wang L, Zhu Y, Li G, Stein DJ, Ipser J, Seedat S, du Plessis S, van den Heuvel LL,
Suarez-Jimenez B, Zhu X, Kim Y, He X, Zilcha-Mano
S, Lazarov A, Neria Y, Stevens JS, Ressler KJ, Jovanovic T, van Rooij SJH, Fani N, Hudson AR, Mueller SC, Sierk A, Manthey
A, Walter H, Daniels JK, Schmahl C, Herzog JI, Říha P, Rektor
I, Lebois LAM, Kaufman ML, Olson EA, Baker JT, Rosso
IM, King AP, Liberzon I, Angstadt M, Davenport ND,
Sponheim SR, Disner SG, Straube T, Hofmann D, Qi R, Lu GM, Baugh LA, Forster
GL, Simons RM, Simons JS, Magnotta VA, Fercho KA, Maron-Katz A, Etkin A, Cotton
AS, O'Leary EN, Xie H, Wang X, Quidé Y, El-Hage W, Lissek S, Berg H, Bruce S, Cisler J, Ross M, Herringa RJ, Grupe DW, Nitschke JB, Davidson RJ, Larson CL,
deRoon-Cassini TA, Tomas CW, Fitzgerald JM, Blackford
JU, Olatunji BO, Kremen WS, Lyons MJ, Franz CE, Gordon EM, May G, Nelson SM,
Abdallah CG, Levy I, Harpaz-Rotem I, Krystal JH, Dennis EL, Tate DF, Cifu DX,
Walker WC, Wilde EA, Harding IH, Kerestes R, Thompson PM, Morey R (2024),
Smaller total and subregional cerebellar volumes in posttraumatic stress
disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup, Mol Psychiatry.
2024 Mar;29(3):611-623. doi:
10.1038/s41380-023-02352-0.
Kim YG, Ravid O, Zheng X, Kim Y, Neria Y, Lee S, He
X, Zhu X (2024), Explaining deep learning-based representations of resting
state functional connectivity data: focusing on interpreting nonlinear patterns
in autism spectrum disorder. Front Psychiatry. 2024 May 20;15:1397093.
doi: 10.3389/fpsyt.2024.1397093. eCollection
2024.
Hansen M, Simon KR, He X, Steele N, Thomas ML,
Noble KG, Merz EC (2024), Socioeconomic factors, sleep timing and duration, and
amygdala resting-state functional connectivity in children. Front Psychiatry.
2024 May 22;15:1373546. doi:
10.3389/fpsyt.2024.1373546. eCollection 2024.
Cheslack-Postava K, Cycowicz YM, Rodriguez-Moreno DV, Amsel
LV, Musa GJ, Ryan M, Bresnahan M, Tang H, Geronazzo-Alman L, Bisaga A, Wang Z, He X, Hoven CW (2024) , Characteristics of Adolescents with and without a Family
History of Substance Use Disorder from a Minority Cohort. Children (Basel).
2024 May 31;11(6):671. doi: 10.3390/children11060671.
He X, Gao Y,
Wang Y, Wang X, Jiang Q, Xu B, Imaging Analysis of Calcium Activities in Brain
Organoid Model of Neuropsychiatric Disorder, Brain Informatics, 2024. December
13-15, Bangkol, Thailand. Short paper and oral
presentation.
Huang L Gong J, Xi Z, He X, Predicting
fMRI Signals from Single-Channel EEG Using Deep Learning, Brain Informatics
2024. December 13-15, Bangkol, Thailand. Abstract and
oral presentation.
Wang Y, Wang Y, Meng Y, Xiao Y, He X, White
Matter Integrity in Youth with Suicide Ideation/Suicide Attempt, Major
Depressive Disorder, and Comorbidities: A Diffusion Tensor Imaging Study, Brain
Informatics, 2024. December 13-15, Bangkol, Thailand.
Short paper and oral presentation.
Tong H, Wang H, Friedman J, Thorp J, Spagna A, He X,
A real time EEG neurofeedback platform to predict students’ attention level,
Real-Time Functional Imaging and Neurofeedback conference (rtFIN 2024),
November 3-6, 2024, Heidelberg, Germany. Poster.
He X, Liu P,
Wang Y, Zhang L, Liu Y, Lee S, Reduced White Matter Integrity in children with
ADHD based on Diffusion Tensor Imaging (DTI) data from the ABCD Study, ABCD
Insights & Innovations Meeting (AIIM). March 4-5, 2024, Bethesda, MD.
Poster.
2023
Zhu X, Kim Y, Ravid O, He X et al., (2023),
Neuroimaging-Based Classification of PTSD Using Data-Driven Computational
Approaches: A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium, NeuroImage. doi:
10.1016/j.neuroimage.2023.120412. Epub 2023 Oct 18.
He X, Moreno D, Hou Z, Cheslack-Postava K, Jiang
Y, Li T, Kishon R, Amsel L, Musa G, Wang Z, Hoven C (2023), Connectivity based
Real-Time fMRI Neurofeedback Training in Youth with a History of Major
Depressive Disorder, https://arxiv.org/abs/2301.11846
Shatto C, Thorp J, Brown A, Friedman J, Shi
J, Gu Z, He X*, Spagna A*,
Neuro-DBER: A flexible neuroscience- and technology-driven framework for the
Scholarship of Teaching & Learning, Cognitive Neuroscience Society Annual
Meeting 2023, San Francisco, March 25-28, 2023.
2022
Tchibozo
M, Kim D, Wang Z, He X (2022),
Emotional Brain State Classification on fMRI Data Using Deep Residual and
Convolutional Networks, https://arxiv.org/abs/2210.17015
Hansen M, Simon K, Strack J, He X, Noble K, Merz E (2022), Socioeconomic Disparities in Sleep
Duration are Associated with Cortical Thickness in Children, Brain and
Behavior. 2022 Dec 27;e2859. doi:
10.1002/brb3.2859
Wang Q, Loh JM, He X, Wang Y (2022), A latent state space model for estimating
brain dynamics from electroencephalogram (EEG) data. Biometrics. https://doi.org/10.1111/biom.13742.
Wang Z, Rodriguez Moreno DV, Cycowicz YM, Amsel LV, Cheslack-Postava
K, He X, Ryan M, Geronazzo-Alman
L, Musa GJ, Bisaga A, Hoven CW (2022). Shapes of
Subcortical Structures in Adolescents with and Without Familial History of
Substance Use Disorder. Human Brain Mapping, 43(9): 2759-2770. doi: 10.1002/hbm.25804
Shi J, He K, He S, Li J, Li M, Brown, Spagna A, He X (2022), A Decoded EEG
Neurofeedback Platform Using Muse2, Real-Time Functional Imaging and
Neurofeedback meeting (rtFIN 2022), Oct 17-21, 2022,
New Haven, CT, USA (poster and oral presentation)
Zheng X, Ravid O, Kim Y, Zhu X, He X, A Denoising Variational Autoencoder for the diagnosis of
Autism based on Resting-state fMRI, Data Science Day poster session, Columbia
University, April 6, 2022, USA.
Kim Y, Ravid O, Neria Y, He X, Zhu X, A Denoising Variational Autoencoder for identifying
PTSD biotypes, Data Science Day, Columbia University, April 6, 2022, USA.
Spagna A, He X,
Imaging the brains of students studying brain imaging: When Neuroscience Meets
the class, Celebration of Teaching and Learning Symposium, Columbia University,
March 29, 2022 USA.
Shatto C, Gu Z, Hui X, Rosario I, Brown A, He X, Spagna A, Who
gets an A+? Discipline Based Education Research meets Neuroscience in the
Classroom, the 29th Annual Meeting of the Cognitive Neuroscience Society on
April 23-26, 2022 in San Francisco, USA.
2021
He X, Rodriguez Moreno D, Cycowicz YM, Wang
Z, Tang H, Amsel L, Cheslack-Postava K, Ryan M, Geronazzo-Alman L, George M, Bisaga
A & Hoven CW (2021). White Matter Integrity and Functional Connectivity in
Adolescents with a Parental History of Substance Use Disorder. Neuroimage:
Reports. https://doi.org/10.1016/j.ynirp.2021.100037
He X, Stefan M, Pagliaccio D, Khamash
L, Fontaine M, Marsh R (2021). A Quality Control Pipeline for Probabilistic
Reconstruction of White-matter Pathways. Journal
of Neuroscience Methods. https://doi.org/10.1016/j.jneumeth.2021.109099.
He X, Pueraro E, Kim Y, Garcia C.M, Maas B, Choi
J, Egglefield D.A, Schiff S, Sneed J.R, Brown P.J,
Brickman A.M, Roose S.P, Rutherford B.R (2021). Association of White Matter
Integrity with Executive Function and Antidepressant Treatment Outcome in
Patients with Late-Life Depression, The
American Journal of Geriatric Psychiatry, doi:
10.1016/j.jagp.2021.01.004
Morenob DR, Cycowicz
Yael, Figner B, Wang Z, He X, Geronazzo-Alman L, Sun X, Cheslack-Postavaa K , Bisaga A, Hoven CW, Amsel L (2021). Delay discounting and
neurocognitive correlates among inner city adolescents with and without family
history of substance use disorder, Developmental
Cognitive Neuroscience, 48:100942.
Ramphal B, Pagliaccio D,
Thomas V. L, He X, Margolis E. A
(2021), Contributions of Cerebellar White Matter Microstructure to Social
Difficulty in Nonverbal Learning Disability. The Cerebellum, https://doi.org/10.1007/s12311-021-01265-4.
He X, Wengler K, Mihali A, Horga G, Decoding
auditory verbal hallucinations based on patterns of neural activity in the
temporal cortex in schizophrenia, the 60th Annual Meeting of the American
College of Neuropsychopharmacology, December 5-8,2021, Puerto Rico
Tchibozo
M, Wang Z, Kim D, He X, Emotional
Brain State Classification on fMRI data using 3D Residual Neural Networks, DSI Health Analytics Center poster session, 2021
Li M, Sun X, He
X, EEGTransformer: Deep Learning based EEG to
fMRI Transformation, Data Science Day
2021 Poster Session.
2020
Rutherford BR, Choi CJ, Choi J, Mass B, He X, O'Boyle K., Sneed J.R., Brown
P.J., Brickman A.M., Wall M.M., Roose S.P.(2020),
Slowed processing speed disrupts expectancy-based placebo effects in late life
depression. Am J Geriatr
Psychiatry, doi:https://doi.org/10.1016/j.jagp.2020.11.001.
Pagliaccio
D, Cha J, He X, Cyr M, Yanes-Lukin
P, Goldberg P, Fontaine M, Rynn M, Marsh R (2020). Structural neural markers of
response to cognitive behavioral therapy in pediatric obsessive-compulsive
disorder, Journal of Child Psychology and
Psychiatry 61(12):1299-1308.
Merz E, He X,
Myers B, Noble K. (2020). Socioeconomic Disadvantage, Chronic Stress, and
Hippocampal Development in Children. Neuroscience
Insights (15): 1-44, https://doi.org/10.1177/2633105520931098.
Lichtin
R, Merz E, He X, Desai P, Simon K,
Melvin S, Maskus E, Noble K (2020), Material
Hardship, Prefrontal Cortex-Amygdala Structure, and Internalizing Symptoms in
Children, Developmental Psychobiology
(63):364-377. https://doi.org/10.1002/dev.22020.
Merz E, He X,
Simon K, Noble K, Parental Stress and Family Routines are Associated with
Cerebral Blood Flow in Children, Poster, SOBP 2020
Simon K.R, Merz E.C, He X, Noble K.G Associations between Environmental Noise Exposure
and Resting-State Functional Connectivity in Children. International Society for Developmental Psychobiology:Virtual Conference September 2020
Simon K.R, Merz E.C, He X, & Noble K.G. Environmental Noise, Language Skills, and
Language-Related Brain Structure in Childhood. Flux Society: Virtual Conference. September 2020
2019
Feng Y, Chuang E, Cycowicz
Y, He X (2019), Motor Imagery
Classification using Cascade ResNet-LSTM, The 25th Annual Meeting of the Organization
for Human Brain Mapping (OHBM), Abstract.
He X, Moreno D, Li T, Tang H, Cycowicz
Y, Wang Z, Amsel L, Musa J, Cheslack-Postava K, Bisaga A, Geronazzo-Alman L,
Bresnahan M, Hoven (2019), Increased Functional Connectivity between DMN and
FPN in Adolescents with Familial History of SUD, The 25th Annual Meeting of the Organization for Human Brain Mapping
(OHBM), Abstract.
Choi J, He X
(2019) , Classification of Autism based on
Resting-state fMRI using Convolutional Neural Networks, The 25th Annual Meeting of the Organization for Human Brain Mapping
(OHBM), Abstract.
Merz E.C., Maskus E.A.,
Melvin S., He X., & Noble K.G.
Socioeconomic disparities in language input are associated with children’s
language-related brain structure and reading skills. Child Development, 28 March 2019.
Merz E.C., Maskus E.A.,
Melvin S., He X., & Noble K.G.
Parental punitive discipline and children’s depressive symptoms: Associations
with striatal volume. Developmental
Psychobiology, 61(6):953-961.
Domakonda M, He X,
Lee S, Cyr M, Marsh R (2019), Increased functional Connectivity between Ventral
Attention and Default Mode Networks in Adolescents with Bulimia Nervosa, Journal of the American Academy of Child and
Adolescent Psychiatry, 58(2):232-241.
2018
He X, Steinberg E, Stefan M, Fontaine, Simpson HB, Marsh R. (2018), Altered
Frontal Inter-hemispheric and Fronto-limbic Structural Connectivity in
Unmedicated Adults with Obsessive-Compulsive Disorder, Human Brain Mapping, DOI: 10.1002/hbm.23883.
Merz EC, He X,
Noble KG (2018), Anxiety, depression, impulsivity, and brain structure in
children and adolescents, NeuroImage: Clinical
20: 243–251.
Choi J, He
X (2018) , Classification of Autism Spectrum
Disorder based on Brain Image using Convolutional Neural Networks, ITU/WHO workshop and Focus Group meeting on
Artificial Intelligence for Health, Nov 14-16, New York, NY
Domakonda M, He X,
Lee S, Cyr M, Marsh R (2018), Increased Functional Connectivity Between Ventral
Attention and Default Mode Networks in Adolescents with Bulimia Nervosa, AACAP’s 65th Annual Meeting, October 22–27,
Seattle, WA, Oral presentation.
Lee YC, Chung EY, He X (2018), Brain State Classification on Functional Near
Infrared Spectroscopy using Convolutional Neural Networks, Annual Data Science Town Hall Meeting, September 28–27, Columbia
University, NYC, Poster.
He X, Huang S, Liu Z, Moreno DR, Amsel L, Musa1 G, Hoven C
(2018), Real-time Brain States Classification using 3D Convolutional Neural
Networks, The 24th Annual Meeting of the
Organization for Human Brain Mapping (OHBM), Jun 17-21, Singapore.
Abstract.
Merz EC, Maskus EA,
He X, Meyer J, Noble KG (2018). The
joint effects of socioeconomic disadvantage and parental depression on
children’s stress physiology and brain development. In M. Stallen
and W. Molenmaker (Chairs), How neuroscience can
contribute to solving societal problems. Symposium
at the Association for Psychological Science (APS) Annual Convention, San
Francisco, California, May.
Desai PM, Merz EC,
Maskus EA, He
X, Noble KG (2018). Socioeconomic disadvantage,
prefrontal cortical structure, and executive function in school-aged children. Poster
presented at the Cognitive Neuroscience Society Annual Meeting, Boston,
Massachusetts, March.
2017
He X, Huang SK, Moreno DR, Kishon R, Amsel L, Musa G,
Noriega A, Wang Z, Hoven C (2017), Connectivity-based Real-time fMRI
Neurofeedback in Youth with a History of Major Depression, the Real-time
Functional Imaging and Neurofeedback, Nov. 29-Dec.1, Nara, Japan
Merz EC, Maskus EA, He X,
Meyer J, Melvin S, Noble KG (2017). Family stress, hair cortisol, and
children’s amygdala and hippocampal volumes. Talk given at the International
Society for Developmental Psychobiology (ISDP) meeting, Washington, D.C.,
November.
Maskus EA, Merz EC, Desai P, He X, Noble KG (2017). Exploring links
among subjective social status, prefrontal cortex structure, and cognitive
skills in children. Poster presented at the Cognitive Development Society
(CDS) Biennial Conference, Portland, Oregon, October
Noble
KG, Piccolo L, Merz EC, Brito N, He, X.
(2017). Socioeconomic inequality modifies links among cortical thickness, age,
and cognition. In J. Booth (Chair), The effect of socioeconomic inequality on
the brain depends on age, cognitive, and environmental factors. Paper
symposium at the SRCD Biennial Meeting, Austin, Texas, April
Domakonda M, He X, Marsh , (2017), A Resting State
Functional Magnetic Resonance Imaging (fMRI) Study of Attention Network
Dysfunction in Adolescents With Bulimia Nervosa, Journal
of the American Academy of Child & Adolescent Psychiatry, October 2017,
Volume 56, Issue 10, Supplement, Page S160.
He X, Moreno DR, Liu Z, Amsel L, Musa G,
Wang Z, Hoven C (2017), Amygdala response may distinguish participants with
history of major depressive disorder, The 23nd
Annual Meeting of the Organization for Human Brain Mapping (OHBM), June 25-29,Vancouver, Canada.
He X, Stefan M, Fontaine M, Cha J, Simpson HB, Marsh R
(2017), A DTI Quality control pipeline for running TRACULA, The 23nd Annual Meeting of the Organization for Human Brain
Mapping (OHBM), June 25-29,Vancouver, Canada.
2016
Piccolo, L.R.,
Merz, E.C., He, X., Sowell, E.R.,
Noble, K.G. (2016). Age-related changes in cortical thickness vary by
socioeconomic status. PLoS One 11(9):e0162511.
He, X., Stefan, M., Terranova, K., Steinglass,
J., Marsh, R. (2016), Altered White Matter Microstructure in Adolescents and
Adults with Bulimia Nervosa, Neuropsychopharmacology
(2016) 1-8. doi: 10.1038/npp.2015.354.
He X, Moreno DR, Geronazzo L, Amsel L, Hoven C, Wang Z (2016), Region of
Interests in Local EPI Space for Real-time fMRI. The 22nd Annual Meeting of
the Organization for Human Brain Mapping (OHBM), June 26-30, Geneva,
Switzerland.
He X, Geronazzo L, Amsel L, Moreno DR, Wang Z,
Fan B, Musa G, Eisenberg R, Doan S, Wicks J, Bresnahan M, Hoven C (2016), White
Matter Abnormalities in Individuals at High Risk of Depression. The 22nd
Annual Meeting of the Organization for Human Brain Mapping (OHBM), June
26-30, Geneva, Switzerland.
Rowny S, He X, Yang R, Zhou S, Prudic J, Javitt D, Hoven C (2016),
Effects of ECT and MST on White Matter Integrity in Patients with Major
Depression. The 22nd Annual Meeting of the Organization for Human Brain
Mapping (OHBM), June 26-30, Geneva, Switzerland.
He X, Stefan M, Fontaine M, Steinberg E, Simpson HB,
Marsh R (2016). Tractography in Unmedicated Adults with
Obsessive-Compulsive Disorder, 2016 Annual Meeting-Society of Biological
Psychiatry (SOBP), May 12-14, Atlanta, Georgia, USA.
He X, Stefan M, Fontaine M, Terranova K, Marsh R
(2016), Using Tractography to Assess Structural Connectivity in
Adolescents with Bulimia Nervosa, 2016 Annual Meeting-Society of Biological
Psychiatry (SOBP), May 12-14, Atlanta, Georgia, USA.
2015
Qiao, J., Wang,
Z., Geronazzo-Alman, L., Amsel, L., Duarte, C., Lee,
S., Musa, G., Long, J., He, X.,
Doan. T, Hirsch, J., Hoven, C. (2015). Brain Activity under Emotional Conflicts
Classifies Adolescents with and without a Familial History of Substance Use
Disorders, Frontiers in Human Neuroscience,
9:219. doi: 10.3389/fnhum.2015.00219
He X, Simpson HB, Marsh R (2015), White Matter
Integrity in Unmedicated Adults with Obsessive-Compulsive Disorder, 2015
Annual Meeting-Society of Biological Psychiatry (SOBP), May 14-16, Toronto,
Canada. Abstract.
He X, Stefan M, Terranova K, Steinglass J, Walsh T,
Marsh R (2015), Analyses of White Matter Integrity in Adolescents and Adults
with Bulimia Nervosa, 2015 Annual Meeting-Society of Biological Psychiatry
(SOBP 2015), May 14-16, Toronto, Canada. Abstract.
He X, Geronazzo
L.A, Lee S, Amsel L, Wang Z, Musa G.J, Duarte C.S, Doan T, Hirsh J, Hirsch,
Hoven C (2015), White matter abnormalities in Adolescents with a Familial
History of Substance Use Disorders. The 21st Annual Meeting of the
Organization for Human Brain Mapping (OHBM), Jun.14-18, Hawaii, USA.
Abstract.
He X, Liu F, Amsel L, Kangarlu A, Gerber A, Wang Z, Musa G, Geronazzo
L, Duarte C, Duan Y, Doan T, Hirsch J, Hoven C (2015), A New Quality Control
Pipeline for Diffusion Tensor Imaging. The 21st Annual Meeting of the
Organization for Human Brain Mapping (OHBM), Jun.14-18, Hawaii, USA.
Abstract
2014
He, X., Liu, W., Li, X., Li, Q., Liu, F., Rauh, V.A., Yin D.,
Bansal, R., Duan, Y., Kangarlu, A., Peterson, B., Xu,
D. (2014). Automated Assessment of Diffusion Tensor Imaging Data Quality Using
the Color Cast of Color-Encoded Fractional Anisotropy Images. Magnetic Resonance Imaging, 32(5):
446-456.
He X, Liu F, Amsel L, Geronazzo
L, Wang Z, Musa G, Duarte C, Kangarlu A, Gerber A,
Duan Y, Qiao J, Doan T, Hirsch J, Hoven C (2014), Quality Criteria for DTI Data
by Assessing Color-Encoded Fractional Anisotropy Images. The 20th Annual
Meeting of the Organization for Human Brain Mapping (OHBM), Jun. 8-12,
Hamburg, Germany. Abstract.
2013
Li, Q., Xu, D., He,
X., Wang, Y., Chen, Z., Liu, H., Xu Q., Guo, F. (2013). AOTF based Molecular Hyperspectral Imaging System
and Its Applications on Nerve Morphometry, Applied
Optics, 52(17):3891-3901.
Li Q, He X, Wang Y, Liu H, Xu D, Guo F (2013), Review of spectral imaging technology
in biomedical engineering: Achievements and challenges, Journal of Biomedical Optics, 18: 100901-1-100901-28. PMID:
24114019
Hu, S., Xu D., Peterson B.S.,
Wang Q.D, He, X., Hu, J., Xu, X., Wei N., Long, D., Huang, M., Zhou, W.,
Xu, W., Zhang, M., Xu, Y. (2013). Association
of Cerebral Networks in Resting State with Sexual Preference of Homosexual Men,
PLoS ONE, 8(3), e59426, Mar. 2013.
He X, Yan X, Hao X, Bansal R,
Wang Z, Peterson B, Xu D (2013), A New Volume Preserved Warping Method for
Measuring Changes of Local Brain Volume, the 19th Annual Meeting of the
Organization for Human Brain Mapping (OHBM), Jun.16-20, Seattle, WA, USA.
Abstract.
2012
Li, Q., Chen,Z., He,X., Wang,Y.,
Liu, H., Xu, Q. (2012). Automatic
identification and quantitative morphometry of unstained spinal nerve using
molecular hyperspectral imaging technology, Neurochemistry,
61(8):1375-84.
Parikh P, Wen Y, He X, Xu D, Peterson B, Delapaz L,
Claassen J (2012), Feasibility of Advanced MR Imaging and Imaging Phenotype of
Ictal-Interictal EEG Patterns in Critically III Patients with Nonstructural,
Severe Brain Injury, American Society of Neuroradiology (ASNR) 50th Annual
Meeting & The Foundation of the ASNR Symposium, New York, NY, USA.
Abstract.
Liu W, Liu X, He X, Zhou Z, Wen Y, Zhou Y, Peterson
BS, Xu D (2012), Spatial normalization of diffusion tensor images with
voxel-wise reconstruction of the diffusion gradient direction, 2nd
International Workshop on Multimodal Brain Image Analysis (MBIA) in conjunction
with MICCAI (pp. 134-146).
2011
He, X., Yang, Z., Tsien J. (2011). A Hierarchical
Probabilistic Model for Rapid Object Categorization in Natural Scenes, PLoS One, 6(5):1-15.
2010
He X, Yang Z, Tsien J (2010),
Object recognition based on hierarchically organized structures of natural
objects, Journal of Vision, 10(7):989,2010, the 10th Annual Meeting of
Vision Sciences Society (VSS2010), Journal of Vision, 10(7):989, Naples,
Florida, USA, May. Poster.
He X, Yang Z, Tsien J (2010), Is categorizing objects
in Natural scenes achievable? Frontiers in Neuroscience 2010, Joint South East Nerve Net (SENN) and Georgia/South Carolina
Neuroscience Consortium Conference (GASCNC), Atlanta, USA, Mar. Travel
award. Oral presentation.
He X, Tsien J, Yang Z (2010),
Object recognition based on hierarchically organized structures of natural
objects. Journal of Vision; 10: 989. http://dx.doi.org/10.1167/10.7.789. Abstract
2009
Shen D, He X, Lu L (2009), A cattle iris segmentation method based on least
square principle. Journal of Image and
Graphics. 14: 2132-2136. (Published in Chinese with English abstract)
He X, Lu Y, Shi P (2009), A new
fake iris detection method, Advances in Biometrics - 3rd International
Conference on Biometrics, (pp. 1139-1146), Alghero, Italy, June.
2008
He, X., Yan, J., Chen G., Shi, P. (2008). Contactless
auto-feedback iris capture design, IEEE
Transactions on Instrumentation and Measurement, 57(7):1369-1375, 2008.
An S, He X, Shi P (2008), Method for fake iris detection based on wavelet
packet decomposition. Measurement &
Control Technology; 27: 9-11. (Published in Chinese with English abstract)
He X, Shi P (2008), Extraction of Complex Wavelet
Features for Iris Recognition, 19th International Conference on Pattern
Recognition (ICPR2008), Florida, USA, Dec.
He X, Lu Y, Shi P (2008), A fake iris detection method
based on FFT and quality assessment, Chinese Conference on Pattern
Recognition, (pp. 316-319), Beijing China, Oct.
2007
He, X., Shi, P. (2007). A New Segmentation Approach for Iris
Recognition Based on Hand-held Capture Device, Pattern Recognition, 40(4):1326-1333.
Wan J, He X, Shi P (2007), An Iris Image
Quality Assessment Method Based on Laplacian of Gaussian Operation, IAPR
Conference on Machine Vision Applications 2007 (MVA 2007) (pp.248-251).
He X, An S, Shi P (2007), Statistical texture analysis-based
approach for fake iris detection using support vector machines, Advances in
Biometrics - International Conference on Biometrics (pp. 540-546).
2006
He, X., Shi, P. (2006), An Efficient Iris Recognition
System, Journal of Computational
Information Systems, 2(4), 1269-1275.
He X, Shi P (2006), A novel iris segmentation method
for hand-held capture device, Advances in Biometrics - International
Conference on Biometrics, (pp. 479-485)
2005
He X, Shi P
(2005), Enhancement method for low quality fingerprint
images. Journal of Data Acquisition &
Processing; 20: 440-443.
He X, Shi P (2005), An efficient iris segmentation
method for recognition, Pattern Recognition and Image Analysis - 3rd
International Conference on Advances in Pattern Recognition, (pp. 120-126)
He X, Shi P: An Eyelid
Estimation Method for Iris Segmentation, Regional Inter-University
Postgraduate Electrical and Electronic Engineering Conference (RIUPEEEC 2005),
Hong Kong, China, Jul. Oral presentation