Artificial Intelligence

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AI: A disruption in science, technology, philosophy, art and society.

Posted by Jair Sánchez, on 10 September 2024

Artificial intelligence has emerged as a beacon of innovation, offering not only groundbreaking solutions but also raising profound questions that remind us of the ever-present challenge of understanding ourselves and what it means to be human. Through intricate mathematical models, we now possess tools to approach and reflect on some of the most profound inquiries

DL4MicEverywhere - Overcoming reproducibility challenges in deep learning microscopy imaging

Posted by Iván Hidalgo-Cenalmor, on 29 July 2024

DL4MicEverywhere is out! Learn about it and how you can apply deep learning workflows on microscopy imaging in reproducible research and in a user-friendly manner across different systems.

An interview with Estibaliz Gómez de Mariscal

Posted by Helen Zenner, on 27 February 2024

At the end of 2023, DL4MicEverywhere was released. The platform aims to make deep learning methods in bioimage analysis more accessible and more reproducible. We caught up with Estibaliz Gómez de Mariscal (Esti), one of the co-leads of the project, to find out more about the platform, and to chat about Esti’s career so far

AI4Life at the 5th NEUBIAS Conference

Posted by Estibaliz Gómez-de-Mariscal, on 26 May 2023

AI4Life recently participated in the 5th NEUBIAS Conference in Porto, Portugal, a two-part event comprising the Defragmentation Training School and the Open Symposium. This conference brought together experts and enthusiasts in the field of BioImage Analysis (BIA) to explore cutting-edge techniques and advancements in the integration of cloud computing. Under the umbrella of AI4Life, there

TrackMate-Oneat: Auto Track correction using deep learning networks

Posted by varun kapoor, on 4 July 2022

During the tracking of motile cells, solving the problem of linking objects between two consecutive timepoints becomes even more complicated, if the cells divide or undergo cell death. In the terms of trajectories, this means the addition of trajectory branches and terminations. However, dividing and dying cells are characteristic in their shape, and leveraging this

The story behind ZeroCostDL4Mic, or How to get started with using Deep Learning for your microscopy data

Posted by Romain Laine, on 18 January 2021

We all hear again and again about Deep Learning (DL), how great it is, how it’s going to revolutionise science, engineering, medicine and work. But where and how is this all happening? If you wonder how you could get started on thinking, let alone using DL on your microscopy data, look no further, we have

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Microscopy-related articles from our journals

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples Development 2024 151: dev202307
filoVision – using deep learning and tip markers to automate filopodia analysis J Cell Sci 2024 137: jcs261274
C omputational tools for quantifying actin filament numbers, lengths, and bundling Biology Open 2024 13: bio.060267

Microscopy-related preprint highlights

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