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The direct observation and research on the subcellular structure is greatly improved by the advances of digital imaging devices and green fluorescent protein (GFP) labeling techniques at the molecular level. However, the digital imaging devices generate huge amount of data, which makes it an urgent task to develop fast, accurate and automatic data processing technologies for the biomedical research...
With the wide application of green fluorescent protein (GFP) in the study of live cell, which leads to a better understanding of biochemical events at subcellular level, there is a surging need for the computer-aided analysis on the huge amount of image sequence data acquired by the advanced microscopy devices. One of such tasks is the motility analysis of the multiple subcellular structures. In this...
Understanding the motility of subcellular particles like organelles, vesicles, or mRNAs is critical to understand how cells regulate delivery of specific proteins from the site of synthesis to the site of action. The goal of this paper is to present a framework of feature selection, matching, and evaluation for the segmentation and tracking of green fluorescent protein (GFP) labeled subcellular structures...
Tagging and tracking protein molecules with the help of laser scanning confocal microscope (LSCM) is a key to better understanding of proteomics in diverse aspects. One challenge of tracking multiple green fluorescent protein (GFP) clusters is how to deal with the interaction between multiple objects, namely splitting and merging. In this paper, we propose a framework to track multiple GFP clusters...
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