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Activity Details


CE_25C Tue, 8/6/2013, 8:30 AM - 5:00 PM W-McGill
Statistical Methods for Neuroimaging Data Analysis — Continuing Education Course
ASA , Biometrics Section
Instructor(s): Hongtu Zhu, UNC-Chapel Hill, Haipeng Shen, UNC-Chapel Hill, Linglong Kong, University of Alberta
With modern imaging techniques, massive imaging data can be observed over both time and space, for example, magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), magnetoencephalography (EMG), and diffusion tensor imaging (DTI), among many others. The subject of medical imaging analysis has exploded from simple algebraic operations on imaging data to advanced statistical and mathematical methods on imaging data. This short course aims to provide a practical introduction to and an overview of recent advanced statistical development to analyze and model medical image data quantitatively. The course material is applicable to a wide variety of medical and biological imaging problems. The topics cover tract-based analysis, multi-scaled statistical methods, fMRI processing methods, diffusion imaging methods, brain image and genetics. While presenting the statistical and mathematical fundamentals, we emphasize the concepts, methods and their real-world implementation. Participants will learn basics that will help them to understand the methods and basic tools built into packages like SPM, FSL, Slicers, and others in order to optimally use them.



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