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Activity Number:
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390
- Functional and High-Dimensional Data
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Type:
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Contributed
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Date/Time:
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Wednesday, August 10, 2022 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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Abstract #322983
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Title:
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Minimax Lower Bounds in High Order Tensor Models with Applications to Neuroimaging
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Author(s):
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Chitrak Banerjee* and LYUDMILA SAKHANENKO and David C Zhu
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Companies:
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Wells Fargo N A and Michigan State University and Michigan State University
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Keywords:
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Minimax lower bounds;
Diffusion tensor imaging;
Tensor modeling
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Abstract:
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High angular resonance diffusion imaging (HARDI) is a popular in-vivo neuroimaging technique used by clinicians for understanding the anatomy of neural fiber structure inside a live human brain. We develop a minimax bound for the integral curve estimator of neural fibers that has an optimal width. Using this minimax bound, we also develop a novel method to compare different neuroimaging protocols. We discuss some interesting simulation results and finally implement this methodology on the HARDI data obtained from a live human brain.
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Authors who are presenting talks have a * after their name.
