Deep learning-based motion artifact removal in functional near-infrared spectroscopy

SIGNIFICANCE: Functional near-infrared spectroscopy (fNIRS), a well-established neuroimaging technique, enables monitoring cortical activation while subjects are unconstrained. However, motion artifact is a common type of noise that can hamper the interpretation of fNIRS data. Current methods that h...

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Detalles Bibliográficos
Autores principales: Gao, Yuanyuan, Chao, Hanqing, Cavuoto, Lora, Yan, Pingkun, Kruger, Uwe, Norfleet, Jack E., Makled, Basiel A., Schwaitzberg, Steven, De, Suvranu, Intes, Xavier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2022
Materias:
Special Section on Computational Approaches for Neuroimaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034734/
https://www.ncbi.nlm.nih.gov/pubmed/35475257
http://dx.doi.org/10.1117/1.NPh.9.4.041406

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034734/
https://www.ncbi.nlm.nih.gov/pubmed/35475257
http://dx.doi.org/10.1117/1.NPh.9.4.041406

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