32 citations · 62 across the 5 of their papers we have counts for
5 papers
The Rise of Data-Driven Microscopy powered by Machine Learning
Leonor Morgado, Estibaliz Gómez-de-Mariscal, Hannah S. Heil +1
Optical microscopy is an indispensable tool in life sciences research, but conventional techniques require compromises between imaging parameters like speed, resolution, field-of-v…
Harnessing Artificial Intelligence To Reduce Phototoxicity in Live Imaging
Estibaliz Gómez-de-Mariscal, Mario Del Rosario, Joanna W Pylvänäinen +2
Fluorescence microscopy, widely used in the study of living cells, tissues, and organisms, often faces the challenge of photodamage. This is primarily caused by the interaction bet…
JDLL: A library to run Deep Learning models on Java bioimage informatics platforms
Carlos Garcia Lopez de Haro, Stephane Dallongeville, Thomas Musset +6
We present JDLL, an agile Java library that offers a comprehensive toolset/API to unify the development of high-end applications of DL for bioimage analysis and to streamline their…
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian +72
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasin…
Search for temporal cell segmentation robustness in phase-contrast microscopy videos
Estibaliz Gómez-de-Mariscal, Hasini Jayatilaka, Özgün Çiçek +3
Studying cell morphology changes in time is critical to understanding cell migration mechanisms. In this work, we present a deep learning-based workflow to segment cancer cells emb…