------ 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. “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]
  2. “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]
  3. “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]
  4. “Anatomy-guided Joint Tissue Segmentation and Topological Correction for 6-month Infant Brain MRI with Risk of Autism”, Human Brain Mapping, 2018. [Li Wang, Gang Li, Ehsan Adeli, Mingxia Liu, Zhengwang Wu, Yu Meng, Weili Lin, Dinggang Shen]
  5. “Functional MRI Registration with Tissue-Specific Patch-Based Functional Correlation Tensors”, Human Brain Mapping, 2018. [Yujia Zhou, Han Zhang, Lichi Zhang, Xiaohuan Cao, Ru Yang, Qianjin Feng, Pew-Thian Yap, Dinggang Shen]
  6. “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