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Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution.


ABSTRACT: Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatial resolution improve the accuracy of cortical surface and thickness estimation compared to the standard 1-millimeter isotropic resolution. Nonetheless, sub-millimeter resolution acquisitions require averaging multiple repetitions to achieve sufficient signal-to-noise ratio and are therefore long and potentially vulnerable to subject motion. We address this challenge by synthesizing sub-millimeter resolution images from standard 1-millimeter isotropic resolution images using a data-driven supervised machine learning-based super-resolution approach achieved via a deep convolutional neural network. We systematically characterize our approach using a large-scale simulated dataset and demonstrate its efficacy in empirical data. The super-resolution data provide improved cortical surfaces similar to those obtained from native sub-millimeter resolution data. The whole-brain mean absolute discrepancy in cortical surface positioning and thickness estimation is below 100 μm at the single-subject level and below 50 μm at the group level for the simulated data, and below 200 μm at the single-subject level and below 100 μm at the group level for the empirical data, making the accuracy of cortical surfaces derived from super-resolution sufficient for most applications.

SUBMITTER: Tian Q 

PROVIDER: S-EPMC7727379 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution.

Tian Qiyuan Q   Bilgic Berkin B   Fan Qiuyun Q   Ngamsombat Chanon C   Zaretskaya Natalia N   Fultz Nina E NE   Ohringer Ned A NA   Chaudhari Akshay S AS   Hu Yuxin Y   Witzel Thomas T   Setsompop Kawin K   Polimeni Jonathan R JR   Huang Susie Y SY  

Cerebral cortex (New York, N.Y. : 1991) 20210101 1


Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatial resolution improve the accuracy of cortical surface and thickness estimation compared to the standard 1-millimeter isotropic resolution. Nonetheless, sub-millimeter resolution acquisitions require averaging multiple repetitions to achieve sufficien  ...[more]

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