Challenges related to artificial intelligence research in medical imaging and the importance of image analysis competitions

Luciano M. Prevedello*, Safwan S. Halabi, George Shih, Carol C. Wu, Marc D. Kohli, Falgun H. Chokshi, Bradley J. Erickson, Jayashree Kalpathy-Cramer, Katherine P. Andriole, Adam E. Flanders

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In recent years, there has been enormous interest in applying artificial intelligence (AI) to radiology. Although some of this interest may have been driven by exaggerated expectations that the technology can outperform radiologists in some tasks, there is a growing body of evidence that illustrates its limitations in medical imaging. The true potential of the technique probably lies somewhere in the middle, and AI will ultimately play a key role in medical imaging in the future. The limitless power of computers makes AI an ideal candidate to provide the standardization, consistency, and dependability needed to support radiologists in their mission to provide excellent patient care. However, important roadblocks currently limit the expansion of this field in medical imaging. This article reviews some of the challenges and potential solutions to advance the field forward, with focus on the experience gained by hosting image-based competitions.

Original languageEnglish (US)
Article numbere180031
JournalRadiology: Artificial Intelligence
Volume1
Issue number1
DOIs
StatePublished - Jan 2019
Externally publishedYes

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Artificial Intelligence
  • Radiological and Ultrasound Technology

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