<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Proceeding</dc:product_type><dc:title>A chi-square type test for time-invariant fiber pathways of the brain: HARDI extension</dc:title><dc:creator>Goo, Juna; Sakhanenko, Lyudmila; Goo, Juna; Sakhanenko, Lyudmila</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Integral curve estimation is a well-established method for reconstructing in vivo nerve fiber pathways in thewhite matter of the brain. Using longitudinal high angular resolution diffusion imaging (HARDI) data, weformulate the longitudinal ensemble of fiber trajectories as an integral curve with the parameter time. The goalof this article is to develop a test statistic to determine whether there are anatomically plausible changes innerve fibers with two directions, such as crossing, kissing, or bending fibers. We envision that rejecting thenull hypothesis could help identify a potential anatomical biomarker for neurodegenerative diseases, such asAlzheimer’s disease.</dc:description><dc:publisher>Zenodo</dc:publisher><dc:date>2024-01-01</dc:date><dc:nsf_par_id>10632673</dc:nsf_par_id><dc:journal_name/><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation/><dc:issn/><dc:isbn/><dc:doi>https://doi.org/10.5281/zenodo.13892241</dc:doi><dcq:identifierAwardId>2111251</dcq:identifierAwardId><dc:subject>Statistics</dc:subject><dc:subject>FOS: Mathematics</dc:subject><dc:subject>kernel smoothing</dc:subject><dc:subject>integral curve</dc:subject><dc:subject>diffusion-weighted magnetic resonance imaging</dc:subject><dc:version_number/><dc:location/><dc:rights>Creative Commons Attribution 4.0 International</dc:rights><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>