@article{Robitaille_Durand_Gardner_Gagné_De Koninck_Lavoie-Cardinal_2018, title={Rating Super-Resolution Microscopy Images With Deep Learning}, volume={32}, url={https://ojs.aaai.org/index.php/AAAI/article/view/12186}, DOI={10.1609/aaai.v32i1.12186}, abstractNote={ <p> With super-resolution optical microscopy, it is now possible to observe molecular mechanisms. The quality of the obtained images vary a lot depending on the samples and the imaging parameters. Moreover, evaluating this quality is a difficult task. In this work, we want to learn the quality function from scores provided by experts. We propose the use of a deep network that output a quality score for a given image. A user study evaluate the quality of the predictions against human expert scores. </p> }, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Robitaille, Louis-Émile and Durand, Audrey and Gardner, Marc-André and Gagné, Christian and De Koninck, Paul and Lavoie-Cardinal, Flavie}, year={2018}, month={Apr.} }