------ 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. “Computational Neuroanatomy of Baby Brains: A Review”, Neuroimage, 2018. [Gang Li*, Li Wang*, Pew-Thian Yap*, Fan Wang, Zhengwang Wu, Yu Meng, Pei Dong, Jaeil Kim, Feng Shi, Islem Rekik, Weili Lin, Dinggang Shen] *Equal contribution
  2. “Exploring Diagnosis and Imaging Biomarkers of Parkinson’s Disease via Iterative Canonical Correlation Analysis Based Feature Selection”, Computerized Medical Imaging and Graphics, 2018. [Luyan Liu, Qian Wang, Ehsan Adeli, Lichi Zhang, Han Zhang,Dinggang Shen]
  3. “Region-adaptive Deformable Registration of CT/MRI Pelvic Images via Learning-based Image Synthesis”, IEEE Transactions on Image Processing, 2018. [Xiaohuan Cao, Jianhua Yang, Yaozong Gao, Qian Wang, Dinggang Shen]
  4. “Medical Image Synthesis with Deep Convolutional Adversarial Networks”, IEEE Transactions on Biomedical Engineering, 2018. [Dong Nie, Roger Trullo, Jun Lian, Li Wang, Caroline Petitjean, Su Ruan, Qian Wang, Dinggang Shen]
  5. “Multi-Channel Multi-Scale Fully Convolutional Network for 3D Perivascular Spaces Segmentation in 7T MR Images”, Medical Image Analysis, 2018. [Chunfeng Lian, Jun Zhang, Mingxia Liu, Xiaopeng Zong, Sheng-Che Hung, Weili Lin, Dinggang Shen]