Reconstructing lost BOLD signal in individual participants using deep machine learning

Reconstructing lost BOLD signal in individual participants using deep machine learning

Signal loss in blood oxygen level‐dependent (BOLD) fMRI can lead to misinterpretation of findings. The authors trained a deep learning model to reconstruct compromised BOLD signal in datasets from healthy participants and in patients whose scans suffered signal loss due to intracortical electrodes....

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Detalles Bibliográficos
Autores principales: Yuxiang Yan, Louisa Dahmani, Jianxun Ren, Lunhao Shen, Xiaolong Peng, Ruiqi Wang, Changgeng He, Changqing Jiang, Chen Gong, Ye Tian, Jianguo Zhang, Yi Guo, Yuanxiang Lin, Shijun Li, Meiyun Wang, Luming Li, Bo Hong, Hesheng Liu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Science
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Acceso en línea:https://doaj.org/article/4329acd981f14858b29114ccd5cf4a4c
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Sumario:Signal loss in blood oxygen level‐dependent (BOLD) fMRI can lead to misinterpretation of findings. The authors trained a deep learning model to reconstruct compromised BOLD signal in datasets from healthy participants and in patients whose scans suffered signal loss due to intracortical electrodes.

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