B1 Non-refereed article in a scientific journal

Deep learning to analyse microscopy images




AuthorsJacquemet Guillaume

PublisherPortland Press Ltd

Publication year2021

JournalBiochemist

Journal name in sourceBiochemist

Volume43

Issue5

First page 60

Last page64

DOIhttps://doi.org/10.1042/bio_2021_167

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/69310675


Abstract

Artificial intelligence (AI)-powered algorithms are now influencing many aspects of our day-to-day life, from providing movies/music recommendations to controlling self-driving cars. These algorithms are also increasingly used in the lab to aid biomedical research. In particular, the ability to analyse and process images using AI is slowly revolutionizing the quality and quantity of data we collect from microscopy images. In fact, AI-based algorithms can now be applied to perform virtually any high-performance image analysis tasks such as classifying images, detecting and segmenting objects, aligning images or improving image quality by removing noise or increasing image resolution. This short feature article briefly underlies the principles behind using AI algorithms to analyse microscopy images with a specific focus on segmentation and denoising.


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Last updated on 2024-26-11 at 14:38