Abstract
Collaborative slide image viewing systems are becoming increasingly important in pathology applications such as telepathology and E-learning. Despite rapid advances in computing and imaging technology, current digital pathology systems have limited performance with respect to remote viewing of whole slide images on desktop or mobile computing devices. In this paper we present a novel digital pathology client-server system that supports collaborative viewing of multi-plane whole slide images over standard networks using multi-touch-enabled clients. Our system is built upon a standard HTTP web server and a MySQL database to allow multiple clients to exchange image and metadata concurrently. We introduce a domain-specific image-stack compression method that leverages real-time hardware decoding on mobile devices. It adaptively encodes image stacks in a decorrelated colour space to achieve extremely low bitrates (0.8 bpp) with very low loss of image quality. We evaluate the image quality of our compression method and the performance of our system for diagnosis with an in-depth user study. Collaborative slide image viewing systems are becoming increasingly important in pathology applications such as telepathology and E-learning. Despite rapid advances in computing and imaging technology, current digital pathology systems have limited performance with respect to remote viewing of whole slide images on desktop or mobile computing devices. In this paper we present a novel digital pathology client-server systems that supports collaborative viewing of multi-plane whole slide images over standard networks using multi-touch enabled clients. Our system is built upon a standard HTTP web server and a MySQL database to allow multiple clients to exchange image and metadata concurrently. © 2013 The Eurographics Association and John Wiley & Sons Ltd.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 227-242 |
| Number of pages | 16 |
| Journal | Computer Graphics Forum |
| Volume | 32 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 13 2013 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: We would like to thank Tobias Hector from Imagination for providing 64bit PVRTexLib and technical support, and the students and faculty at UNIST ECE for participating the user study. This work has been partially supported by the year of 2011 research fund of UNIST, Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A1039929), NSF grants PHY 0938178, OIA 1125087, NIH grant 2R44MH088088-03, the Conte Center at Harvard (NIMH), Transformative R-01 (NIH), the Gatsby Charitable Trust to JWL, Department of Molecular and Cellular Biology at Harvard University, NVIDIA, Google and the Intel Science and Technology Center for Visual Computing.