KEYWORDS: Image retrieval, Medical imaging, Image storage, Databases, Data storage, Clinical trials, Web services, Binary data, Data communications, Stanford Linear Collider
Medical image based biomarkers are being established for therapeutic cancer clinical trials, where image assessment is
among the essential tasks. Large scale image assessment is often performed by a large group of experts by retrieving
images from a centralized image repository to workstations to markup and annotate images. In such environment, it is
critical to provide a high performance image management system that supports efficient concurrent image retrievals in a
distributed environment. There are several major challenges: high throughput of large scale image data over the Internet
from the server for multiple concurrent client users, efficient communication protocols for transporting data, and effective
management of versioning of data for audit trails. We study the major bottlenecks for such a system, propose and evaluate a
solution by using a hybrid image storage with solid state drives and hard disk drives, RESTfulWeb Services based protocols
for exchanging image data, and a database based versioning scheme for efficient archive of image revision history. Our
experiments show promising results of our methods, and our work provides a guideline for building enterprise level high
performance medical image management systems.
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