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ANALYSIS OF HYPERSPECTRAL DATA
Hyperspectral imaging uses optical techniques to image the spatial and chemical characteristics
of tissue samples. In particular, Fourier-Transform
Infrared (FT-IR) and Raman Spectroscopy can be used to determine the classification and distribution of cells
in tissue samples using only optical and computational techniques. I am currently working with the
Chemical Imaging and Structures Laboratory
to perform classification and visualization of biological tissue samples. The goal of this work is
to provide improved tools for research and clinical diagnosis of disease.
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MODELING AND VISUALIZATION OF TISSUE MICROSTRUCTURE
Tissue microstructure is tremendously complex,
consisting of vast microvascular networks and highly
interconnected neural networks. One of the major challenges in
biology is understanding the three-dimensional structure of tissue data
at its highest resolution. Even with emerging high-throughput
imaging technology that allows us to capture these data sets, we are
still faced with the challenge of making large and complex data sets fit
for human interpretation.
My current work includes:
- Visualizing the relationships between cells and microvessels (video)
- Interactive visualization of large filament networks
- Methods and metrics for validating segmentation
- Segmentation of serial EM data
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KNIFE-EDGE SCANNING MICROSCOPY
A major focus of my research at the
Brain Networks
Lab has been the development of new high-throughput imaging
techniques. In particular, we have developed a new microscopy technique, known
as Knife-Edge Scanning Microscopy, which allows us to efficiently image
large-scale tissue microstructure. This technology has allowed us
to image large tissue volumes (approx. 1 cubic cm), creating
terabytes of data describing some of the most complex
structures ever seen.
My current work includes:
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