A knowledge-anchored integrative image search and retrieval system

Selnur Erdal, Umit V. Catalyurek, Philip R.O. Payne, Joel Saltz, Jyoti Kamal, Metin N. Gurcan

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Clinical data that may be used in a secondary capacity to support research activities are regularly stored in three significantly different formats: (1) structured, codified data elements; (2) semi-structured or unstructured narrative text; and (3) multi-modal images. In this manuscript, we will describe the design of a computational system that is intended to support the ontology-anchored query and integration of such data types from multiple source systems. Additional features of the described system include (1) the use of Grid services-based electronic data interchange models to enable the use of our system in multi-site settings and (2) the use of a software framework intended to address both potential security and patient confidentiality concerns that arise when transmitting or otherwise manipulating potentially privileged personal health information. We will frame our discussion within the specific experimental context of the concept-oriented query and integration of correlated structured data, narrative text, and images for cancer research.

Original languageEnglish
Pages (from-to)166-182
Number of pages17
JournalJournal of Digital Imaging
Volume22
Issue number2
DOIs
StatePublished - Apr 2009

Keywords

  • Grid computing
  • Image retrieval
  • Information retrieval
  • Ontologies
  • Text mining

Fingerprint

Dive into the research topics of 'A knowledge-anchored integrative image search and retrieval system'. Together they form a unique fingerprint.

Cite this