An analysis of histogram-based thresholding algorithms
CVGIP: Graphical Models and Image Processing
Cell image segmentation for diagnostic pathology
Advanced algorithmic approaches to medical image segmentation
Shape-Based Image Indexing and Retrieval for Diagnostic Pathology
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
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A better understanding of cell behavior is very important in drug and disease research. Cell size, shape, and motility may play a key role in stem-cell specialization or cancer development. However the traditional method of inferring these values manually is such an onerous task that automated methods of cell tracking and segmentation are in high demand. Image cytometry is a practical approach to measure and extract cell properties from large volumes of microscopic cell images. As an important application of image cytometry, this paper presents a probabilistic model based cell tracking method to locate and associate HSCs in phase contrast microscopic images. The proposed cell tracker has been successfully applied to track HSCs based on the most probable identified cell locations and probabilistic data association.