Deep Generative Adversarial Networks for Thin-Section Infant MR Image Reconstruction

Deep Generative Adversarial Networks for Thin-Section Infant MR Image Reconstruction

Due to their high spatial resolution, thin-section magnetic resonance (MR) images serve as ideal medical images for brain structure investigation and brain surgery navigation. However, compared with the clinically widely used thick-section MR images, thin-section MR images are less available due to...

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Bibliographic Details
Main Authors: Jiaqi Gu, Zeju Li, Yuanyuan Wang, Haowei Yang, Zhongwei Qiao, Jinhua Yu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Deep learning
infant magnetic resonance (MR) images
super-resolution reconstruction
thick-section
thin-section
Online Access:https://ieeexplore.ieee.org/document/8721701/

Internet

https://ieeexplore.ieee.org/document/8721701/

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