Feature-Centric Content Analysis for Bioimaging Informatics

Summary

This study aims to develop novel algorithms for content analysis in microscopic images, such as segmentation of cell nuclei, detection of certain cell structures, and tracing of cell changes over time. Such algorithms would be valuable to turn image data into useful biological knowledge. This study will focus on computer vision methodologies in feature extraction and learning-based modeling.

Supervisor(s)

Associate Professor Tom Weidong Cai

Research Location

Computer Science

Program Type

Masters/PHD

Synopsis

Great advances in biological tissuelabeling and automated microscope imaging have revolutionized how biologists visualize molecular, sub-cellular structures and study their respective functions. How to interpret such image datasets in aquantitative and automative way has become a major challenge in current computational biology. The essential methods of bioimaging informatics involve generation, visualization, analysis and management.

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Keywords

Bioimaging informatics, microscopic imaging, Computer vision, Image processing

Opportunity ID

The opportunity ID for this research opportunity is: 1883

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