CloudBrain-ReconAI: A Cloud Computing Platform for MRI Reconstruction and Radiologists’ Image Quality Evaluation

Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI). Here, we develop CloudBrain-ReconAI, an online cloud computing platform, for algorithm deployment, fast and blind reader study. This platform supports online image reconstruction using state-of-the-art artificial intelligence and compressed sensing algorithms with applications for fast imaging (Cartesian and non-Cartesian sampling) and high-resolution diffusion imaging. Through visiting the website, radiologists can easily score and mark images. Then, automatic statistical analysis will be provided.

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Publication Details

Journal
IEEE Transactions on Cloud Computing
Published
2024-10-01
DOI
https://doi.org/10.1109/tcc.2024.3476418
Citations
7
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
1.29
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article

CloudBrain-ReconAI: A Cloud Computing Platform for MRI Reconstruction and Radiologists’ Image Quality Evaluation

Jianjun Zhou, Biao Qu, Liuhong Zhu, Qing Hong et al.
7 citations
IEEE Transactions on Cloud Computing
Advanced X-ray and CT Imaging
1.29
article

CloudBrain-ReconAI: A Cloud Computing Platform for MRI Reconstruction and Radiologists’ Image Quality Evaluation

Jianjun Zhou, Biao Qu, Liuhong Zhu, Qing Hong, Yirong Zhou, Xiaobo Qu, Di Guo, Jianzhong Lin, Zi Wang, Jiyang Dong, Taishan Kang, Chen Qian, Jiayu Li, Yu Hu
article en
7 citations

Abstract

Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI). Here, we develop CloudBrain-ReconAI, an online cloud computing platform, for algorithm deployment, fast and blind reader study. This platform supports online image reconstruction using state-of-the-art artificial intelligence and compressed sensing algorithms with applications for fast imaging (Cartesian and non-Cartesian sampling) and high-resolution diffusion imaging. Through visiting the website, radiologists can easily score and mark images. Then, automatic statistical analysis will be provided.

IEEE Transactions on Cloud ComputingVol. 12(4)
China Mobile (China) (CN), Xiamen University (CN), Fudan University (CN), Zhongshan Hospital of Xiamen University (CN), Xiamen University of Technology (CN)
Openalex Percentile: Top 21%
Advanced X-ray and CT Imaging
1.29
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CloudBrain-ReconAI: A Cloud Computing Platform for MRI Reconstruction and Radiologists’ Image Quality Evaluation — Jianjun Zhou, Biao Qu, et al. · IEEE Transactions on Cloud Computing (2024) | TGRS Research Map | TGRS