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Rosella Denise Trò

As seen in: Nature, BioRxiv
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Articles

Automated tracking of the brown algal parasite Eurychasma dicksonii with deep learning

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By Davide Cangelosi, Yacine Badis, Rosella Denise Trò, Behnoud Shafiezadeh Kenari, Shayan Alvansazyazdi, Serena Testi
| Nature Verified
Abstract This study presents an automated real-time tracking approach for Eurychasma dicksonii, an intracellular parasite affecting brown algae, using deep learning applied to time-lapse microscopy video analysis. Traditionally, parasite detection and tracking rely on manual observation, resulting in a time-consuming, operator-dependent process prone to inaccuracies.
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Data-driven characterization of Preterm Birth through intramodal Diffusion MRI

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By Domenico Tortora, Mariasavina Severino, Rosella Denise Trò, Monica Roascio
| BioRxiv
Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website.
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