Binghao Chai, Christoforos Efstathiou, Haoran Yue, Viji M Draviam
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引用次数: 0
Abstract
The growth of artificial intelligence (AI) has led to an increase in the adoption of computer vision and deep learning (DL) techniques for the evaluation of microscopy images and movies. This adoption has not only addressed hurdles in quantitative analysis of dynamic cell biological processes but has also started to support advances in drug development, precision medicine, and genome-phenome mapping. We survey existing AI-based techniques and tools, as well as open-source datasets, with a specific focus on the computational tasks of segmentation, classification, and tracking of cellular and subcellular structures and dynamics. We summarise long-standing challenges in microscopy video analysis from a computational perspective and review emerging research frontiers and innovative applications for DL-guided automation in cell dynamics research.
期刊介绍：
Trends in Cell Biology stands as a prominent review journal in molecular and cell biology. Monthly review articles track the current breadth and depth of research in cell biology, reporting on emerging developments and integrating various methods, disciplines, and principles. Beyond Reviews, the journal features Opinion articles that follow trends, offer innovative ideas, and provide insights into the implications of new developments, suggesting future directions. All articles are commissioned from leading scientists and undergo rigorous peer-review to ensure balance and accuracy.
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