Journal of Digital Imaging

, 17:235

Addressing the Coming Radiology Crisis—The Society for Computer Applications in Radiology Transforming the Radiological Interpretation Process (TRIP™) Initiative

  • Katherine P. Andriole
  • and the SCAR TRIP™ Subcommittee: Richard L. Morin, PhD, Chair, TRIP™ Subcommittee, Ronald L. Arenson, MD, John A. Carrino, MD, MPH, Bradley J. Erickson, MD, PhD, Steven C. Horii, MD, David W. Piraino, MD, Bruce I. Reiner, MD, J. Anthony Seibert, PhD, Eliot Siegel, MD
Article

DOI: 10.1007/s10278-004-1027-1

Cite this article as:
Andriole, K.P. & and the SCAR TRIP™ Subcommittee: Richard L. Morin, PhD, Chair, TRIP™ Subcommittee, Ronald L. Arenson, MD, John A. Carrino, MD, MPH, Bradley J. Erickson, MD, PhD, Steven C. Horii, MD, David W. Piraino, MD, Bruce I. Reiner, MD, J. Anthony Seibert, PhD, Eliot Siegel, MD J Digit Imaging (2004) 17: 235. doi:10.1007/s10278-004-1027-1

Abstract

The Society for Computer Applications in Radiology (SCAR) Transforming the Radiological Interpretation Process (TRIP™) Initiative aims to spearhead research, education, and discovery of innovative solutions to address the problem of information and image data overload. The initiative will foster interdisciplinary research on technological, environmental and human factors to better manage and exploit the massive amounts of data. TRIP™ will focus on the following basic objectives: improving the efficiency of interpretation of large data sets, improving the timeliness and effectiveness of communication, and decreasing medical errors. The ultimate goal of the initiative is to improve the quality and safety of patient care. Interdisciplinary research into several broad areas will be necessary to make progress in managing the ever-increasing volume of data. The six concepts involved are human perception, image processing and computer-aided detection (CAD), visualization, navigation and usability, databases and integration, and evaluation and validation of methods and performance. The result of this transformation will affect several key processes in radiology, including image interpretation; communication of imaging results; workflow and efficiency within the health care enterprise; diagnostic accuracy and a reduction in medical errors; and, ultimately, the overall quality of care.

Keywords

large data sets, radiological image interpretation paradigm 

Copyright information

© SCAR (Society for Computer Applications in Radiology) 2004

Authors and Affiliations

  • Katherine P. Andriole
    • 1
  • and the SCAR TRIP™ Subcommittee: Richard L. Morin, PhD, Chair, TRIP™ Subcommittee, Ronald L. Arenson, MD, John A. Carrino, MD, MPH, Bradley J. Erickson, MD, PhD, Steven C. Horii, MD, David W. Piraino, MD, Bruce I. Reiner, MD, J. Anthony Seibert, PhD, Eliot Siegel, MD
  1. 1.Department of Radiology, Brigham and Women’s Hospital, Harvard Medical SchoolBoston

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