Recycling diagnostic MRI for empowering brain morphometric research – Critical & practical assessment on learning-based image super-resolution

Recycling diagnostic MRI for empowering brain morphometric research – Critical & practical assessment on learning-based image super-resolution

Preliminary studies have shown the feasibility of deep learning (DL)-based super-resolution (SR) technique for reconstructing thick-slice/gap diagnostic MR images into high-resolution isotropic data, which would be of great significance for brain research field if the vast amount of diagnostic MRI d...

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Bibliographic Details
Main Authors: Gaoping Liu, Zehong Cao, Qiang Xu, Qirui Zhang, Fang Yang, Xinyu Xie, Jingru Hao, Yinghuan Shi, Boris C. Bernhardt, Yichu He, Feng Shi, Guangming Lu, Zhiqiang Zhang
Format: article
Language:EN
Published: Elsevier 2021
Subjects:
Deep-learning
Image super-resolution
Brain MRI
Morphometric analysis
Practical assessment
Neurosciences. Biological psychiatry. Neuropsychiatry
RC321-571
Online Access:https://doaj.org/article/ff567b0fdbc84ce991ece2a84fce771a
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