Professor Margrit Betke of the Computer Science Department received a National Science Foundation award entitled “RI: Small: Using Humans in the Loop to Collect High-quality Annotations from Images and Time-lapse Videos of Cells.” Congratulations to Margrit!
Sequences of microscopy images of live cells are analyzed by cell biologists to understand cellular processes, for example, to prevent cancer or design bio-materials for wound healing. Research progress is slowed or compromised when scientists find the image analysis efforts too labor-intensive to do themselves and the automation methods too numerous, unreliable, or difficult to use. The project develops image-analysis software to leverage human and computer resources together, in particular on the internet, to create high-quality image interpretations. An expansive benchmark study of detection, segmentation, and tracking algorithms for analyzing images of live cells is conducted, followed by the development of computer-vision approaches to the algorithms. Methods are designed for quantifying annotations, and then a tool is built to use the expertise of cell biologists to judge and select methods that analyze cell images. Crowd-sourcing experiments in which internet workers analyze images are designed and conducted. The quality of these lay workers’ annotations is compared to the quality of annotations by cell biologists and automated methods. Finally, a machine learning system is developed that automatically determines which types of cell images or videos can be analyzed accurately with or without human involvement.