Technology
ReScale4D is a systematic approach for determining optimal image resolution in deep learning-based microscopy segmentation, balancing accuracy with acquisition/storage costs. Following this approach, researchers can improve the sustainability and cost-effectiveness of bioimaging studies by reducing data and computing needs while optimising microscopy techniques.
Publications featuring Rescale4DL
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mAIcrobe: an open-source framework for high-throughput bacterial image analysis António D. Brito, Dominik Alwardt, Beatriz de P. Mariz, Sérgio R. Filipe, Mariana G Pinho, Bruno M. Saraiva, Ricardo Henriques Preprint published in bioRxiv, October 2025 Technologies: DeepBacs (), mAIcrobe (), Rescale4DL () and ZeroCostDL4Mic () Funded by: EMBO, ERC, H2021 and H2022 DOI: 10.1101/2025.10.21.683709 |
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ReScale4DL: Balancing Pixel and Contextual Information for Enhanced Bioimage Segmentation Mariana G. Ferreira, Bruno M. Saraiva, António D. Brito, Mariana G. Pinho, Ricardo Henriques, Estibaliz Gómez-de-Mariscal Preprint published in bioRxiv, April 2025 Technologies: BioImage Model Zoo (), DeepBacs (), DL4MicEverywhere (), NanoPyx (), Rescale4DL () and ZeroCostDL4Mic () Funded by: CZI, EMBO, ERC, H2021 and H2022 DOI: 10.1101/2025.04.09.647871 |
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