Managing and querying whole slide images

Abstract

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.

Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data

“…We have reference implementations that integrate with our PAIS, [30][31][32] although it is important to note that other standards exist to store annotations including one developed by the Open Microscopy Environment Consortium (OME-TIFF). Unlocking the true value and latent content embedded in these images, however, requires the ability to semantically describe imaging features in understandable and reproducible terminologies.…”

The Emergence of Pathomics

“…The OMERO (OME Remote Objects) extension of the OME platform is designed to serve as a central repository of pathology image data [47]. Wang et al [2,48] developed PIDB (Pathology Image Database System) and PAIS (Pathology Analytical Imaging Standards) models to represent pathology image metadata and image analysis results and metadata that draw from the AIM (Annotation and Image Markup) model [49] and extend it with data elements Fig. 4 Deep learning image analysis pipeline to generate a Featuremap.…”

OpenSlide: A vendor-neutral software foundation for digital pathology

“…OpenSlide is also used in the backends of online slide management systems such as Simagis Live[28] and Emory's Pathology Image Database System. [29] The VIPS image processing system,[19] a toolkit for analysis and manipulation of very large images, supports reading slide files using OpenSlide.…”