TY - JOUR
T1 - Deep learning to analyse microscopy images
AU - Jacquemet, Guillaume
N1 - Publisher Copyright:
© October 2021 The Authors. Published by Portland Press Limited under the Creative Commons Attribution License 4.0 (CC BY-NC-ND)
PY - 2021
Y1 - 2021
N2 - 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-basedalgorithms 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
AB - 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-basedalgorithms 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
UR - http://www.scopus.com/inward/record.url?scp=85123886274&partnerID=8YFLogxK
U2 - 10.1042/bio_2021_167
DO - 10.1042/bio_2021_167
M3 - Article
AN - SCOPUS:85123886274
SN - 0954-982X
VL - 43
SP - 60
EP - 64
JO - Biochemist
JF - Biochemist
IS - 5
ER -