Digital pathology: Data-intensive frontier in medical imaging

Lee A.D. Cooper, Alexis B. Carter, Alton B. Farris, Fusheng Wang, Jun Kong, David A. Gutman, Patrick Widener, Tony C. Pan, Sharath R. Cholleti, Ashish Sharma, Tahsin M. Kurc, Daniel J. Brat, Joel H. Saltz

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Pathology is a medical subspecialty that practices the diagnosis of disease. Microscopic examination of tissue reveals information enabling the pathologist to render accurate diagnoses and to guide therapy. The basic process by which anatomic pathologists render diagnoses has remained relatively unchanged over the last century, yet advances in information technology now offer significant opportunities in image-based diagnostic and research applications. Pathology has lagged behind other healthcare practices such as radiology where digital adoption is widespread. As devices that generate whole slide images become more practical and affordable, practices will increasingly adopt this technology and eventually produce an explosion of data that will quickly eclipse the already vast quantities of radiology imaging data. These advances are accompanied by significant challenges for data management and storage, but they also introduce new opportunities to improve patient care by streamlining and standardizing diagnostic approaches and uncovering disease mechanisms. Computer-based image analysis is already available in commercial diagnostic systems, but further advances in image analysis algorithms are warranted in order to fully realize the benefits of digital pathology in medical discovery and patient care. In coming decades, pathology image analysis will extend beyond the streamlining of diagnostic workflows and minimizing interobserver variability and will begin to provide diagnostic assistance, identify therapeutic targets, and predict patient outcomes and therapeutic responses.

Original languageEnglish
Article number6155059
Pages (from-to)991-1003
Number of pages13
JournalProceedings of the IEEE
Volume100
Issue number4
DOIs
StatePublished - Apr 2012
Externally publishedYes

Funding

Manuscript received May 16, 2011; revised September 1, 2011; accepted October 20, 2011. Date of publication February 17, 2012; date of current version March 21, 2012. This work was supported in part by SAIC/NCI under Contracts HHSN261200800001E and N01-CO-12400 from the National Cancer Institute, by the National Heart Lung and Blood Institute under Grant R24HL085343, by the National Library of Medicine under Grants 1R01LM011119-01 and R01LM009239, by the National Institutes of Health under Grant RC4MD005964, by the Clinical and Translational Science Awards program under PHS Grant UL1RR025008, and by the Biomedical Information Science and Technology Initiative program under Grant P20 EB000591. L. A. D. Cooper, F. Wang, J. Kong, D. A. Gutman, P. Widener, T. C. Pan, S. R. Cholleti, A. Sharma, T. M. Kurc, and J. H. Saltz are with the Center for Comprehensive Informatics, Emory University, Atlanta, GA 30306 USA (e-mail: [email protected]; [email protected]). A. B. Carter, A. B. Farris, and D. J. Brat are with the Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30306 USA (e-mail:[email protected]; [email protected]; [email protected]).

FundersFunder number
PHSUL1RR025008, P20 EB000591
National Institutes of HealthRC4MD005964
National Heart, Lung, and Blood InstituteR24HL085343
National Cancer InstituteHHSN261200800001E, N01-CO-12400
U.S. National Library of Medicine1R01LM011119-01, R01LM009239
Science Applications International Corporation

    Keywords

    • Biomedical imaging
    • biomedical informatics
    • digital pathology
    • image analysis
    • virtual microscopy

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