Aspects of the analysis of cell imagery: from shape to understanding

Li, C. (2024)

Doctoral Thesis

In this thesis, we have studied cell images from two types of cells, including pollen grains and the immune cells, neutrophils. These images are captured using a bright field microscope and a confocal microscope. We aim to analyze the insight in the understanding of the content of these images. In order to do these analyses, we need computational methods. The two main tasks are the classification of pollen images and the dynamic analysis of neutrophils through tracking in time-lapse sequences. In this study, we have demonstrated the use of deep learning methods for different kinds of cell imagery and shown the potential for future use while illustrating pitfalls, but also presenting efficient new algorithmic approaches.

• Cell image analysis
• Pollen classification
• Feature extraction
• Neutrophil tracking
• Deep learning
• Viterbi algorithm

• All authors: Li, C.
• Supervisor: Verbeek, F.J.
• Co-supervisor: Cao, L.
• Committee: Bonsangue, M.M.; Bäck, T.H.W.; Batenburg, K.J.; Gravendeel, B.; Frazao Muzitano, M.
• Qualification: Doctor (dr.)
• Awarding Institution: Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University
• Date: 2024-06-27
• ISBN (print): 9789465061368