------ Image Display, Enhancement, and Analysis (IDEA) Group

UNC IDEA group consists of the IDEA Lab in the Department of Radiology and the Image Analysis Core Lab in the Biomedical Research Imaging Center (BRIC). The IDEA lab is devoted to the development of novel image analysis methods and tools, and their applications to various clinical research and trials. The developed methods include deformable registration (HAMMER), deformable segmentation (AFDM), and multivariate pattern classification algorithms. These methods have been applied to various studies on brain diseases and development (including MCI, AD, Schizophrenia, and Neonate Development Study), heart, breast cancer, and prostate cancer. The image analysis core in BRIC supports the image storage and analysis needs of scientists in UNC. It also provides services for brain structural and functional analysis, small animal imaging analysis, visualization, and others.

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New Papers:

  1. “Polyp Detection during Colonoscopy using a Regression-based Convolutional Neural Network with a Tracker“, Pattern Recognition, 2018. [Ruikai Zhang, Yali Zheng, Carmen C. Y. Poona, Dinggang Shen, James Y. W. Lau]
  2. “Data-driven Graph Construction and Graph Learning: A Review”, Neurocomputing, 2018. [Lishan Qiao, Limei Zhang, Songcan Chen, Dinggang Shen]
  3. “Sparse Multi-View Task-Centralized Ensemble Learning for ASD Diagnosis Based on Age- and Sex-related Functional Connectivity Patterns”, IEEE Transactions on Cybernetics, 2018. [Jun Wang, Qian Wang, Han Zhang, Jiawei Chen, Shitong Wang, Dinggang Shen]
  4. “Multi-Task Prediction of Infant Cognitive Scores from Longitudinal Incomplete Neuroimaging Data”, NeuroImage, 2018. [Ehsan Adeli, Yu Meng, Gang Li, Weili Lin, Dinggang Shen]
  5. “Discovering Cortical Sulcal Folding Patterns in Neonates Using Large-scale Dataset”, Human Brain Mapping, 2018. [Yu Meng, Gang Li, Li Wang, Weili Lin, John H Gilmore, Dinggang Shen]