UNC IDEA Group

------ 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.

Follow our new articles automatically by clicking 'Follow new articles' in this web and providing your email address.

 

New Papers:

  1. "Automatic Labeling of MR Brain Images by Hierarchical Learning of Atlas Forests”, Medical Physics, 2016. [Lichi Zhang, Qian Wang, Yaozong Gao, Guorong Wu, Dinggang Shen]
  2. "Accurate Segmentation of CT Male Pelvic Organs via Regression-based Deformable Models and Multi-task Random Forests”, IEEE Transactions on Medical Imaging, 2016. [Yaozong Gao, Yeqin Shao, Jun Lian, Andrew Z. Wang, Ronald C. Chen, Dinggang Shen]
  3. "State-Space Model with Deep Learning for Functional Dynamics Estimation in Resting-State fMRI”, Neuroimage 2016. [Heung-Il Suk, Chong-Yaw Wee, Seong-Whan Lee, Dinggang Shen]
  4. "Relationship Induced Multi-template Learning for Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment”, IEEE Transactions on Medical Imaging, 2016. [Mingxia Liu, Daoqiang Zhang, Dinggang Shen]
  5. "eHUGS: Enhanced Hierarchical Unbiased Graph Shrinkage for Efficient Groupwise Registration", PLOS ONE, 2015. [Guorong Wu, Xuewei Peng, Shihui Ying, Qian Wang, Pew-Thian Yap, Dan Shen, Dinggang Shen]