TY - GEN
T1 - Managing and querying whole slide images
AU - Wang, Fusheng
AU - Oh, Tae W.
AU - Vergara-Niedermayr, Cristobal
AU - Kurc, Tahsin
AU - Saltz, Joel
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Image data management
KW - PACS
KW - Pathology analytical imaging standards
KW - Whole slide image
UR - https://www.scopus.com/pages/publications/84861852753
U2 - 10.1117/12.912388
DO - 10.1117/12.912388
M3 - Conference contribution
SN - 9780819491176
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Photonic Crystal Materials and Devices X
T2 - Photonic Crystal Materials and Devices X
Y2 - 16 April 2012 through 19 April 2012
ER -