Note that my former uchicago email address is being phased out.
I am a mathematically inclined applied computer scientist, with specific expertise in the fields of visualization, image processing, and image analysis. On the methodical side, I am particularly interested in tensor decompositions, higher-order tensor fields, and feature-based visualization; on the application side, most of my work has been in the area of neuroscience and medicine, especially on Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) and High Angular Resolution Diffusion Imaging (HARDI). I am currently extending the scope of my work to a stronger use of machine learning techniques, modeling of uncertainty, and applications to a wider range of imaging modalities.
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Learning a Reliable Estimate of the Number of Fiber
Directions in Diffusion MRI |
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Computational Vascular Morphometry for the
Assessment of Pulmonary Vascular Disease based on Scale-Space
Particles |
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Segmenting Thalamic Nuclei: What Can We Gain From HARDI? |
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Topological Features in 2D Symmetric Higher-Order Tensor Fields |
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Towards Resolving Fiber Crossings with Higher Order Tensor Inpainting |
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Superquadric Glyphs for Symmetric Second-Order Tensors |
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Multi-Diffusion-Tensor Fitting via Spherical Deconvolution: A Unifying Framework |
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Feature Extraction for DW-MRI Visualization: The State of the Art and Beyond |
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A Maximum Enhancing Higher-Order Tensor Glyph |
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Crease Surfaces: From Theory to Extraction and Application to Diffusion Tensor MRI |
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Feature Extraction for Visual Analysis of DW-MRI Data |
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A Higher-Order Structure Tensor |
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Estimating Crossing Fibers: A Tensor Decomposition Approach |
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Using Eigenvalue Derivatives for Edge Detection in DT-MRI Data |
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Virtual Klingler Dissection: Putting Fibers into Context |
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Topological Visualization of Brain Diffusion MRI Data |
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Segmentation of DT-MRI Anisotropy Isosurfaces |
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Flexible Segmentation and Smoothing of DT-MRI Fields Through a Customizable Structure Tensor |