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.
- "Learning-based Deformable Image Registration for Infant MR Images in the First Year of Life”, Medical Physics, 2016. [Shunbo Hu, Lifang Wei, Yaozong Gao, Yanrong Guo, Guorong Wu, Dinggang Shen]
- "Progressive Multi-Atlas Label Fusion by Dictionary Evolution”, Medical Image Analysis, 2016. [Yantao Song, Guorong Wu, Khosro Bahrami, Quansen Sun, Dinggang Shen]
- "View-Aligned Hypergraph Learning for Alzheimer’s Disease Diagnosis with Incomplete Multi-Modality Data”, Medical Image Analysis, 2016. [Mingxia Liu, Jun Zhang, Pew-Thian Yap, Dinggang Shen]
- "Improving Estimation of Fiber Orientations in Diffusion MRI Using Inter-Subject Information Sharing”, Scientific Reports, 2016. [Geng Chen, Pei Zhang, Ke Li, Chong-Yaw Wee, Yafeng Wu*, Dinggang Shen*, Pew-Thian Yap*] *Co-corresponding authors
- "Deep Learning in Medical Image Analysis”, Annual Review of Biomedical Engineering, 2016. [Dinggang Shen, Guorong Wu, Heung-Il Suk]