Medical Image Computing

Dr. Yakang Dai (戴亚康) is a professor in the Medical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology (SIBET), Chinese Academy of Sciences. He also serves the University of Chinese Academy of Sciences
He is interested in Medical Image Analysis (MRI, CT, PET, etc), EEG/MEG Signal Processing, 3D Ultrasound Imaging, 3D Visualization, and Software Platform for Medical Image Computing(Email: 

Education Background:
He received his B.S. degree in Electrical Engineering from Hunan University in 2004, and Ph.D. degree in Computer Applied Technology from Institute of Automation, Chinese Academy of Sciences in 2009. He did postdoctoral researches in Biomedical Engineering at the University of Minnesota in 2009-2011, and in Medical Image Analysis at the University of North Carolina at Chapel Hill in 2011-2012.

Research Experiences:
He worked in the IDEA Lab at the University of North Carolina at Chapel Hill. His research focused on medical image analysis and software platform. With the group, he developed Infant Brain Extraction and Analysis Toolbox (iBEAT) and 4D Adult Brain Extraction and Analysis Toolbox (aBEAT), which are toolboxes with graphical user interfaces for processing infant and 4D adult brain MR images, respectively. The toolboxes include functions of image preprocessing, brain extraction, tissue segmentation, and brain labeling. The Linux-based standalone software package was released in December, 2011. The toolbox can be applied to various infant brain studies (cross-sectional, longitudinal, etc). The iBEAT and aBEAT have been downloaded over 700 times.

He worked in the Biomedical Functional Imaging and Neuroengineering Laboratory at the University of Minnesota in 2009-2011. He was devoted to the development of the eConnectome (Electrophysiological Connectome) software which is an open-source MATLAB toolbox for imaging brain functional connectivity from electrophysiological signals. The first beta version of the eConnectome supporting EEG/ECoG was released on March 12, 2010, and the first full version was released on August 19, 2010. The version 2.0 beta supporting connectivity analysis from MEG was released on June 1, 2011. The eConnectome has been downloaded over 500 times.

He studied in the Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences in 2004-2009. He was involved in the research and development of Medical Imaging Toolkit (MITK) and 3D Medical Image Processing and Analyzing System (3DMed), and was the leader of the MITK team in 2007-2008. The MITK and 3DMed have achieved more than 20,000 downloads. He participated in, as a core member, the algorithm and software development for programs including 863 Program of China, National Natural Science Foundation of China and Scientific Research Equipment Development Program of Chinese Academy of Sciences.