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.
- "Hierarchical High-Order Functional Connectivity Networks and Selective Feature Fusion for MCI Classification”, Neuroinformatics, 2017. [Xiaobo Chen, Han Zhang, Dinggang Shen]
- "Spatio-Angular Consistent Construction of Neonatal Diffusion MRI Atlases”, Human Brain Mapping, 2017. [Behrouz Saghafi ∗, Jaeil Kim ∗, Geng Chen, Feng Shi, Pew-Thian Yap, Dinggang Shen] * Co-first authors
- "Multi-Task Diagnosis for Autism Spectrum Disorders Using Multi-Modality Features: A Multi-Center Study”, Human Brain Mapping, 2017. [Jun Wang, Qian Wang, Jialin Peng, Dong Nie, Feng Zhao, Minjeong Kim, Han Zhang, Chong-Yaw Wee, Shitong Wang, Dinggang Shen]
- "Joint Prediction of Longitudinal Development of Cortical Surfaces and White Matter Fibers from Neonatal MRI”, NeuroImage, 2017. [Islem Rekik, Gang Li, Yap Pew-Thian, Geng Chen, Weili Lin, Dinggang Shen]
- “Image Mosaicking Using SURF Features of Line Segments,” PLOS ONE, 2017. [Zhanlong Yang, Dinggang Shen, Pew-Thian Yap]