AI4Life-MDC24 Challenge data: W2S Dataset

<p>This is a subset of the W2S dataset: Zhou, R., El Helou, M., Sage, D., Laroche, T., Seitz, A., S&uuml;sstrunk, S. (2020). W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM Mapping. In: Bartoli, A., Fusiello, A. (eds) Computer Vision &ndash; ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science(), vol 12535. Springer, Cham. <a href="https://doi.org/10.1007/978-3-030-66415-2_31">https://doi.org/10.1007/978-3-030-66415-2_31</a><br><br>The selected <strong>subset</strong> contains 120 images with three channels, acquired using a conventional fluorescence widefield, in the form of a single multi-channel tiff file.<br><br><span><span><span><span>Code, data, and a copy of the original paper is available at&nbsp; <a href="https://github.com/IVRL/w2s" target="_blank" rel="noopener noreferrer">https://github.com/IVRL/w2s</a></span></span></span></span><br><br>AI4Life has received funding from the European Union&rsquo;s Horizon Europe research and innovation programme under grant agreement number 101057970. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.</p>