DCAE-CEST
DCAE-CEST: : The DCAE-CEST method can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solu
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How to cite: : Kurmi Y, Viswanathan M, Zu Z. Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder. Magn Reson Med. 2024; 1-16. doi: 10.1002/mrm.30228
DCAE-CEST: The DCAE-CEST method can learn the most important features of the CEST Z-spectrum and provide the effective denoising solution with high fidelity of the data.
Key words: Chemical exchange saturation transfer (CEST), amide proton transfer (APT), nuclear Overhauser effect, deep learning, denoising convolutional autoencoder (DCAE), tumor
Contributors: DCAE-CEST: Yashwant Kurmi, Malvika Viswanathan, Zhongliang Zu
https://github.com/CESTlabZu/DCAE-CEST
Cite As
Yashwant Kurmi (2026). DCAE-CEST (https://github.com/CESTlabZu/DCAE-CEST), GitHub. Retrieved .
General Information
- Version 1.0.1 (21.7 MB)
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View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
Versions that use the GitHub default branch cannot be downloaded
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.1 | Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder |
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| 1.0.0 |
