Managing and Querying Whole Slide Images.

High-resolution pathology images provide rich information about the morphological and functional characteristics of biological systems, and are transforming the field of pathology into a new era. To facilitate the use of digital pathology imaging for biomedical research and clinical diagnosis, it is essential to manage and query both whole slide images (WSI) and analytical results generated from images, such as annotations made by humans and computed features and classifications made by computer algorithms. There are unique requirements on modeling, managing and querying whole slide images, including compatibility with standards, scalability, support of image queries at multiple granularities, and support of integrated queries between images and derived results from the images. In this paper, we present our work on developing the Pathology Image Database System (PIDB), which is a standard oriented image database to support retrieval of images, tiles, regions and analytical results, image visualization and experiment management through a unified interface and architecture. The system is deployed for managing and querying whole slide images for In Silico brain tumor studies at Emory University. PIDB is generic and open source, and can be easily used to support other biomedical research projects. It has the potential to be integrated into a Picture Archiving and Communications System (PACS) with powerful query capabilities to support pathology imaging.