Cell Detection with Deep Learning – Frontiers in Digital Health

Call for Papers:

Cell Detection with Deep Learning – Frontiers in Digital Health

About this Research Topic

Automated cell detection is a very important step in image analysis of cells. Given rapid advancements in microscopy technology, life-science researchers acquire big data in cell biology for breakthrough scientific discovery. However, manual analysis of high-content and high-throughput screening for quantifying and capturing cellular features at a large scale is a formidable task. Such challenge in image analysis of biological cells calls for the aid of artificial intelligence to produce fast and accurate analysis results. This research topic focuses on the use of state-of-the-art deep learning methods for cell detection. Authors are invited to submit papers that address the application of deep learning to the following areas, but not limited to

  • Cell segmentation

  • Cell counting

  • Dynamic cell tracking

  • Cell shape analysis

  • Quantification of cell distribution

  • Quantification of cell morphology

  • Detection of organelles in single cells

Important Date

  • Paper submission due: 01 October 2020

Topic Editors

Tuan D. Pham

Saudi Aramco Center for Artificial Intelligence

Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia

Ran Su

School of Computer Software

College of Intelligence and Computing

Tianjin University, Tianjin, China

Changming Sun

CSIRO Data61, Sydney, Australia

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