------ 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. “Multi-label Nonlinear Matrix Completion with Transductive Multi-task Feature Selection for Joint MGMT and IDH1 Status Prediction of Patient with High-Grade Gliomas”, IEEE Transactions on Medical Imaging, 2018. [Lei Chen*, Han Zhang*, Junfeng Lu*, Kimhan Thung, Abudumijiti Aibaidula, Luyan Liu, Songcan Chen, Lei Jin, Jinsong Wu, Qian Wang, Liangfu Zhou, Dinggang Shen]  * Co-first authors
  2. “Robust Multi-Label Transfer Feature Learning for Early Diagnosis of Alzheimer’s Disease”, Brain Imaging and Behavior, 2018. [Bo Cheng, Mingxia Liu, Daoqiang Zhang, Dinggang Shen]
  3. “Sub-network Kernels for Measuring Similarity of Brain Connectivity Networks in Disease Diagnosis”, IEEE Transactions on Image Processing, 2018. [Biao Jie, Mingxia Liu, Daoqiang Zhang, Dinggang Shen]
  4. “3D Fully Convolutional Networks for Multi-Modal Isointense Infant Brain Image Segmentation”, IEEE Transactions on Cybernetics, 2018. [Dong Nie, Li Wang, Ehsan Adeli, Cuijing Lao, Weili Lin, Dinggang Shen]
  5. Conversion and Time-to-Conversion Predictions of Mild Cognitive Impairment using Low-Rank Affinity Pursuit Denoising and Matrix Completion, Medical Image Analysis, 2018. [Kim-Han Thung, Pew-Thian Yap, Ehsan Adeli, Seong-Whan Lee, Dinggang Shen]