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of 4
pro vyhledávání: '"Keejin Yoon"'
Autor:
Keejin Yoon, Derek B. Archer, Margareta A. Clarke, Seth A. Smith, Ipek Oguz, Gary Cutter, Junzhong Xu, Francesca Bagnato
Publikováno v:
Frontiers in Neurology, Vol 13 (2022)
PurposeIn this cross-sectional, proof-of-concept study, we propose that using the more pathologically-specific neurite orientation dispersion and density imaging (NODDI) method, in conjunction with high-resolution probabilistic tractography, white ma
Externí odkaz:
https://doaj.org/article/933131350b7641d4bb1edddbd7628aca
Autor:
Kristin P. O'Grady, Sanjana Satish, Quinn R. Owen, Bailey A. Box, Francesca Bagnato, Anna J. E. Combes, Sarah R. Cook, Holly James Westervelt, Haley R. Feiler, Richard D. Lawless, Asha Sarma, Shekinah D. Malone, Josephine M. Ndolo, Keejin Yoon, Richard D. Dortch, Baxter P. Rogers, Seth A. Smith
Publikováno v:
Frontiers in Neurology, Vol 13 (2022)
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) can probe tissue biochemistry in vivo with high resolution and sensitivity without requiring exogenous contrast agents. Applying CEST MRI at ultrahigh field provides advant
Externí odkaz:
https://doaj.org/article/7e6f0c9bcddd4db7b2d3c663d7ca50ae
Autor:
Jiacheng Wang, Hao Li, Han Liu, Dewei Hu, Daiwei Lu, Keejin Yoon, Kelsey Barter, Francesca Bagnato, Ipek Oguz
Automated segmentation of multiple sclerosis (MS) lesions from MRI scans is important to quantify disease progression. In recent years, convolutional neural networks (CNNs) have shown top performance for this task when a large amount of labeled data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7bdd03a7ea37c38fb36be516d5bdad2
Autor:
Francesca Bagnato, Si Gao, Seth A. Smith, Keejin Yoon, Richard D. Dortch, Sijin Wen, Junzhong Xu, Dhairya A. Lakhani, Amalie Chen
Publikováno v:
J Neuroimaging
Background and purpose Axonal injury is a key player of disability in persons with multiple sclerosis (pwMS). Yet, detecting and measuring it in vivo is challenging. The neurite orientation dispersion and density imaging (NODDI) proposes a novel fram
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f05bd6635c3e9c59bb77f7ea58b76e74
https://doi.org/10.1111/jon.12876
https://doi.org/10.1111/jon.12876