Automated Semantic Indexing of Imaging Reports to Support Retrieval of Medical Images in the Multimedia Electronic Medical Record

H. J. Lowe; I. Antipov; W. Hersh; C. A. Smith; M. Mailhot

doi:10.1055/s-0038-1634413

Methods of Information in Medicine, Table of Contents

Methods Inf Med 1999; 38(04/05): 303-307
DOI: 10.1055/s-0038-1634413

Original Article

Schattauer GmbH

Automated Semantic Indexing of Imaging Reports to Support Retrieval of Medical Images in the Multimedia Electronic Medical Record

Authors

H. J. Lowe

¹Division of Center for Biomedical Informatics, University of Pittsburgh, USA
I. Antipov

¹Division of Center for Biomedical Informatics, University of Pittsburgh, USA
W. Hersh

²Division of Medical Informatics and Outcomes Research, Oregon Health Sciences University, USA
C. A. Smith

¹Division of Center for Biomedical Informatics, University of Pittsburgh, USA
M. Mailhot

²Division of Medical Informatics and Outcomes Research, Oregon Health Sciences University, USA

Abstract

This paper describes preliminary work evaluating automated semantic indexing of radiology imaging reports to represent images stored in the Image Engine multimedia medical record system at the University of Pittsburgh Medical Center. The authors used the SAPHIRE indexing system to automatically identify important biomedical concepts within radiology reports and represent these concepts with terms from the 1998 edition of the U.S. National Library of Medicine’s Unified Medical Language System (UMLS) Metathesaurus. This automated UMLS indexing was then compared with manual UMLS indexing of the same reports. Human indexing identified appropriate UMLS Metathesaurus descriptors for 81% of the important biomedical concepts contained in the report set. SAPHIRE automatically identified UMLS Metathesaurus descriptors for 64% of the important biomedical concepts contained in the report set. The overall conclusions of this pilot study were that the UMLS metathesaurus provided adequate coverage of the majority of the important concepts contained within the radiology report test set and that SAPHIRE could automatically identify and translate almost two thirds of these concepts into appropriate UMLS descriptors. Further work is required to improve both the recall and precision of this automated concept extraction process.

Keywords

Computerized Medical Records Systems - Abstracting and Indexing - Unified Medical Language System - Medical Imaging - Multimedia

Full Text

References

REFERENCES
1 Lomas DJ, Dixon AK. Radiology. 100 years and running: the medical imaging revolution. Lancet 1995; 346 Suppl: S20.
2 Honeyman JC, Frost MM, Huda W, Loeffler W, Ott M, Staab EV. Picture archiving and communications systems (PACS). Curr Probl Diagn Radiol 1994; 23: 101-58.
3 O’Brien MJ, Sotnikov AV. Digital imaging in anatomic pathology. Am J Clin Pathol 1996; 106 4 Suppl 1 S25-32.
4 Thomas JD, Nissen SE. Digital storage and transmission of cardiovascular images: what are the costs, benefits and timetable for conversion?. Heart 1996; 76: 13-7.
5 Kenet RD. Digital imaging in dermatology. Clin Dermatol 1995; 13: 381-92.
6 Lowe HJ. Multimedia Electronic Medical Record Systems. Acad Med 1999; 74: 146-52.
7 Dayhoff RE, Saddler C, Kirin G, Frank SA, Kuzmak PM. Extending the multimedia patient record across the wide area network. Proc AMIA Annu Fall Symp. 1996: 653-7.
8 Lowe HJ, Buchanan BG, Cooper GF, Kaplan B, Vries JK. Image Engine: an Integrated Multimedia Clinical Information System. In: Greenes (Editor),. Proceedings of the IMIA Eight World Congress on Medical Informatics (MEDINFO). Vancouver BC: 1995: 421-5.
9 Lowe HJ, Buchanan BG, Cooper GF, Vries JK. Building a Medical Multimedia Database System to Integrate Clinical Information. An Application of High Performance Computing and Communications Technology. Bull Med Libr Assoc 1995; 83 (Suppl. 01) 57-64.
10 Lowe HJ, Walker WK, Vries JK. Using Agent-Based Technology to Create a Cost Effective, Integrated, Multimedia View of the Electronic Medical Record. In: Gardner RM. ed. Proceedings of the Nineteenth Annual Symposium on Computer Applications in Medical Care; New Orleans, LA; October-November. Philadelphia: Hanley & Belfus; 1995: 441-4.
11 Lowe HJ, Antipov I, Walker WK, Polonkey SE, Naus GJ. WebReport: A World Wide Web Based Clinical Multimedia Reporting System.. Proceedings of 1996 AMIA Annual Fall Symposium. Journal of the American Medical Informatics Association Supplement; 314-8.
12 Lowe HJ, Hersh W, Arnott Smith C. The Multimedia Medical Record as a Virtual Library. A Multidimensional Model for Indexing the content of Medical Images using the Unified Medical Language System AMIA. 1998. Spring Congress.;
13 Bidgood Jr WD, Horii SC, Prior FW, Van Syckle DE. Understanding and using DICOM, the data interchange standard for biomedical imaging. Am Med Inform Assoc 1997; 4: 199-212.
14 Lindberg DA, Humphreys BL, McCray AT. The Unified Medical Language System. Method Inform Med 1993; 32: 281-91.
15 Humphreys B. et al. The Unified Medical Language System: an informatics research collaboration. J Am Med Inform Assoc 1998; 5: 1-11.
16 Hersh WR, Leone TJ. The SAPHIRE server. Proceedings of the 19th Annual Symposium on Computer Applications in Medical Care. 1995: 858-62.
17 Hersh W, Donohoe L. SAPHIRE International: a tool for cross-language information retrieval. Proceedings of the Annual AMIA Fall Symposium. 1998. Orlando: FL: Hanley-Belfus: in press.;
18 McCray AT, Razi AM, Bangalore AK, Browne AC, Stavri PC. The UMLS Knowledge Source Server-a Versatile Internet-Based Research Tool. Proc AMIA Fall Symp 1996: 164-8.
19 Honeyman IC, Huda W, Frost MM, Palmer CK, Staab EV. Picture Archiving and Communications System Bandwidth and Storage Requirements. J Digital Imaging 1996; 9: 60-6.
20 Chu WW. et al. KMED: A Knowledge-Based Multimedia Medical Distributed Database System. Information Systems 1994; 19: 33-54.
21 Liu Y, Rothfus W, Kanade T. Content-based 3D Neuroradiologic Image Retrieval: Preliminary Results. IEEE Workshop on Content-Based Access of Image and Video Databases in conjunction with ICCV ’98.; Bombay, India: 1998
22 Flickner M, Sawhney H, Niblack W. et al. Query by Image and Video Content: The QBIC System. IEEE Computer; September 1995: 23-31.
23 Robinson GP, Tagare HD, Duncan JS, Jaffe CC. Medical image collection indexing: shape-based retrieval using KD-trees. Comput Med Imaging Graph 1996; 20: 209-17.
24 Betal D, Roberts N, Whitehouse GH. Segmentation and numerical analysis of microcalcifications on mammograms using mathematical morphology. Br J Radiol 1997; 70: 903-17.
25 Saiviroonporn P, Robatino A, Zahajszky J, Kikinis R, Jolesz FA. Real-time interactive three-dimensional segmentation. Acad Radiol 1998; 5: 49-56.
26 Ravela S, Manmatha R. Image Retrieval by Appearance. SIGIR: 1997: 278-85.