CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation
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Abstract (arXiv)
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 to fast imaging and high-resolution diffusion imaging. Through visiting the website, radiologists can easily score and mark the images. Then, automatic statistical analysis will be provided. CloudBrain-ReconAI is now open accessed at https://csrc.xmu.edu.cn/CloudBrain.html and will be continually improved to serve the MRI research community.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Dec 2022.
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Citing papers per year: 2023: 2; 2024: 1; 2025: 1.
4 papers.
- 2023One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstructioncited by 14
- 2024Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRIcited by 4
- 2023Cloud-Magnetic Resonance Imaging System: In the Era of 6G and Artificial Intelligencecited by 2
- 2025Robust High-Resolution Multi-Organ Diffusion MRI Using Synthetic-Data-Tuned Prompt Learningcited by 0
- 2025Robust High-Resolution Multi-Organ Diffusion MRI Using Synthetic-Data-Tuned Prompt Learning17 Oct 2025
- 2024Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRI24 Feb 2024
- 2023Cloud-Magnetic Resonance Imaging System: In the Era of 6G and Artificial Intelligence18 Oct 2023
- 2023One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction25 Jul 2023