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Neuroscience

D-Index
74
Citations
22755
World Ranking
2088
National Ranking
993

Overview

Gang Li is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research primarily spans the fields of Medicine and Neuroscience, with a focus on pediatrics, radiology, cognitive neuroscience, computer vision, and artificial intelligence.

Their main research topics include functional brain connectivity studies, advanced neuroimaging techniques and applications, neonatal and fetal brain pathology, fetal and pediatric neurological disorders, advanced MRI techniques and applications, domain adaptation and few-shot learning, and medical image segmentation techniques.

Frequent coauthors collaborating with Gang Li are:

  • Li Wang
  • Weili Lin
  • Zhengwang Wu
  • Dinggang Shen
  • Fenqiang Zhao

The scientist's publication venues typically include:

  • UNC Libraries
  • Lecture Notes in Computer Science
  • IEEE Transactions on Medical Imaging
  • arXiv (Cornell University)
  • Medical Image Analysis

Recent research papers authored or coauthored by Gang Li are:

  • iBEAT V2.0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction, 2023, Nature Protocols
  • Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge, 2021, IEEE Transactions on Medical Imaging
  • Deep Fusion of Brain Structure-Function in Mild Cognitive Impairment, 2021, Medical Image Analysis
  • A deep learning model for detection and tracking in high-throughput images of organoid, 2021, Computers in Biology and Medicine
  • Synergetic effect of O-POSS and T-POSS to enhance ablative resistant of phenolic-based silica fiber composites via strong interphase strength and ceramic formation, 2022, Composites Part A Applied Science and Manufacturing

Best Publications

  • The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development.

    Brittany R. Howell;Martin A. Styner;Wei Gao;Wei Gao;Pew-Thian Yap

  • Dynamic Development of Regional Cortical Thickness and Surface Area in Early Childhood

    Amanda E. Lyall;Feng Shi;Xiujuan Geng;Sandra Woolson

  • Review of methods for functional brain connectivity detection using fMRI

    Kaiming Li;Lei Guo;Jingxin Nie;Gang Li

  • Mapping Longitudinal Development of Local Cortical Gyrification in Infants from Birth to 2 Years of Age

    Gang Li;Li Wang;Feng Shi;Amanda E. Lyall

  • LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

    Li Wang;Yaozong Gao;Feng Shi;Gang Li

  • Smartwatch-Based Wearable EEG System for Driver Drowsiness Detection

    Gang Li;Boon-Leng Lee;Wan-Young Chung

  • High-order resting-state functional connectivity network for MCI classification

    Xiaobo Chen;Han Zhang;Yue Gao;Chong Yaw Wee

  • Mapping Region-Specific Longitudinal Cortical Surface Expansion from Birth to 2 Years of Age

    Gang Li;Jingxin Nie;Li Wang;Feng Shi

  • Modeling Rett Syndrome Using TALEN-Edited MECP2 Mutant Cynomolgus Monkeys

    Yongchang Chen;Yongchang Chen;Juehua Yu;Yuyu Niu;Yuyu Niu;Dongdong Qin

  • Benchmark on Automatic Six-Month-Old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge

    Li Wang;Dong Nie;Guannan Li;Elodie Puybareau

  • Segmentation of neonatal brain MR images using patch-driven level sets.

    Li Wang;Feng Shi;Gang Li;Yaozong Gao

  • Computational neuroanatomy of baby brains: A review.

    Gang Li;Li Wang;Pew Thian Yap;Fan Wang

  • High glucose-induced expression of inflammatory cytokines and reactive oxygen species in cultured astrocytes.

    J. Wang;G. Li;Z. Wang;X. Zhang

  • Mapping Longitudinal Hemispheric Structural Asymmetries of the Human Cerebral Cortex From Birth to 2 Years of Age

    Gang Li;Jingxin Nie;Li Wang;Feng Shi

  • Spatial Patterns, Longitudinal Development, and Hemispheric Asymmetries of Cortical Thickness in Infants from Birth to 2 Years of Age

    Gang Li;Weili Lin;John H. Gilmore;Dinggang Shen

  • Construction of 4D high-definition cortical surface atlases of infants: Methods and applications

    Gang Li;Li Wang;Feng Shi;John H. Gilmore

  • iBEAT V2.0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction

    Unknown

  • Spatial distribution and longitudinal development of deep cortical sulcal landmarks in infants

    Yu Meng;Gang Li;Weili Lin;John H. Gilmore

  • Axonal Fiber Terminations Concentrate on Gyri

    Jingxin Nie;Lei Guo;Kaiming Li;Kaiming Li;Yonghua Wang

  • Structural and Maturational Covariance in Early Childhood Brain Development

    Xiujuan Geng;Gang Li;Zhaohua Lu;Wei Gao

  • Measuring the dynamic longitudinal cortex development in infants by reconstruction of temporally consistent cortical surfaces.

    Gang Li;Jingxin Nie;Li Wang;Feng Shi

  • Integration of sparse multi-modality representation and anatomical constraint for isointense infant brain MR image segmentation.

    Li Wang;Feng Shi;Yaozong Gao;Gang Li

Frequent Co-Authors

Tianming Liu
Tianming Liu University of Georgia
Lei Guo
Lei Guo Beijing University of Posts and Telecommunications
Han Zhang
Han Zhang ShanghaiTech University
Kaiming Li
Kaiming Li Sichuan University
Yaozong Gao
Yaozong Gao United Imaging Healthcare (China)
L. Stephen Miller
L. Stephen Miller University of Georgia
Wei Gao
Wei Gao Cedars-Sinai Medical Center
Kathryn L. Humphreys
Kathryn L. Humphreys Vanderbilt University
Tianzi Jiang
Tianzi Jiang Chinese Academy of Sciences

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Related Online Degrees & Career Pathways

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Students balancing passion and practicality may also want to review easiest college majors with high pay. This can help identify alternative or dual-degree pathways that lead to rewarding, high-paying careers while pursuing an interest in neuroscience.

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