Bioimage informatics

Bioimage informatics is a subfield of bioinformatics and computational biology. It is most related to using computational techniques to analyze bioimages, especially cellular and molecular images, at large scale and high throughput, with the goal to mine useful knowledge out of complicated and heterogeneous image and related meta data. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems.

This field is in quick growth in recent years, apparently due to the flood of complicated molecular and cellular microscopic images produced in a series of projects that create compelling challenges for the image computing community.

Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources.