A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop

P. Langlotz, Curtis; Allen, Bibb; J. Erickson, Bradley; Kalpathy–Cramer, Jayashree; Bigelow, Keith; S. Cook, Tessa; E. Flanders, Adam; P. Lungren, Matthew; S. Mendelson, David; D. Rudie, Jeffrey; Wang, Ge; Kandarpa, Krishna

doi:10.1148/radiol.2019190613

Public

A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop

Published in Radiology • Apr 16, 2019

Authors:

Curtis P. Langlotz

Bibb Allen

Bradley J. Erickson

Abstract

Imaging research laboratories are rapidly creating machine learning systems that achieve expert human performance using open-source methods and tools. These artificial intelligence systems are being developed to improve medical image reconstruction, noise reduction, quality assurance, triage, segmen...

Subject

Artificial intelligence

Medicine

Medical imaging

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