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Tools
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| Item Type: | Dataset |
|---|---|
| Title: | DeBCR: a deep learning framework for microscopy image enhancement (Python API) |
| Creators: |
Yushkevich, Artsemi  ORCID: https://orcid.org/0000-0002-8729-9281, Li, Rui ORCID: https://orcid.org/0000-0002-3085-5267, Chu, Xiaofeng ORCID: https://orcid.org/0000-0001-6801-3949, Kudryashev, Misha ORCID: https://orcid.org/0000-0003-3550-6274 and Manukyan, Artur ORCID: https://orcid.org/0000-0002-0441-9517
|
| Abstract: | DeBCR - a deep learning framework for microscopy images restoration; Python API package deposition. DeBCR is a deep learning framework for microscopy images restoration such as denoising and deconvolution (resolution enhancement). DeBCR implements the m-rBCR model - a multi-scale image restoration model, proposed by us earlier (Li, Kudryashev, Yakimovich, ECCV 2024, 2025). |
| Keywords: | Image Processing, Image Restoration, Image Enhancement, Deep Learning, BCR, BCR-Net, m-rBCR, Denoising, Deblurring, Deconvolution, Confocal Microscopy, Widefield Microscopy, Fluorescence Microscopy, Light Microscopy |
| Source: | Zenodo |
| Publisher: | CERN |
| Date: | 18 February 2026 |
| Official Publication: | https://doi.org/10.5281/zenodo.17673860 |
| Related to: |
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