Jun Zhang of the Department of Biostatistics defends her dissertation on "Interpretable Analysis of Multivariate Functional Data".
The Joint Statistical Meetings, known simply as "JSM", is the largest gathering of statisticians held annually in North American. Faculty and student presenters from the Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations. Our students often receive top awards and participate in the affiliated career marketplace at the event.
Meetings of the Eastern North American Region of the International Biometric Society (a.k.a. "ENAR meetings") are held in late March or early April each year and reflect the broad interests of the Society, including both quantitative techniques and application areas. Faculty and student presenters from the Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations.
The neuroimaging field faces significant challenges in the study of neurodegenerative diseases such as Alzheimer's Disease (AD): it utilizes various imaging techniques and software packages that were originally developed and characterized for neuroimaging studies of healthy brains. These software often require extensive in-house modification that make analysis pipelines opaque and very hard to reproduce even in healthy populations. Additionally, automated segmentations of the brain are very difficult in the presence of brain pathologies such as white matter hyperintensities (WMH). WMHs appear as hyperintense areas in magnetic resonance imaging (MRI) and are frequently found in AD population's brain. WMHs present a challenge for standard segmentation algorithms that misclassify WMHs as gray matter (GM) and for co-registration with other imaging modalities such as Positron Emission Tomography (PET) that is used to detect amyloid plague in the AD brains. An overview of reproducibility in the context of healthy brain is presented along with some newly developed improvements for segmentation methods in presence of WMHs in AD. A high dimensional longitudinal data analysis model is introduced. The proposed methods showed significant improvement in tissue classification for AD.
Last Updated On Monday, October 15, 2018 by Tang, Lu
Created On Friday, August 24, 2018
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