Combining medical image processing, pattern recognition, and machine learning techniques, our research aims to study the brain changes that occur in aging and neurodegenerative disorders, which require novel methodologies able to exploit information in medical images. Here is a summary of the main research projects that the lab is currently working on.
Accurate detection of healthy and pathological tissue types from brain MRIs is a requirement in many clinical and research applications. The variabilities in tissue intensity profiles caused by differences in scanner models, acquisition protocols, as well as age and potential presence of pathologies make this task challenging. Developing tools that can be reliably used in multi-center and multi-scanner studies of healthy and diseased populations is therefore essential. We develop MRI preprocessing and analysis tools for detection and assessment of various brain structures and pathologies.
Understanding the impact of the mechanisms and interactions through which neurodegenerative and cerebrovascular pathologies lead to cognitive impairment is essential for developing strategies for prevention of cognitive decline and dementia in aging populations. Using the tools that we develop, we study the brain changes that occur in different neurodegenerative disease populations as well as their associations to risk factors and clinical outcomes.
In-vivo MRIs allow researchers and clinicians to detect early signs of disease and investigate its longitudinal trajectories. However, MRI is not sufficiently specific for determining the underlying pathology of these alterations. Linking the abnormalities that are visible on MRI to post-mortem neuropathology information can lead to more sensitive MRI biomarkers, more refined interpretation of in-vivo findings, and help determine potential disease mechanisms. We acquire post-mortem and histology data of brains with various neurodegnerative disorders, and develop tools to process and analyze these images.