The Diagnostic Imagination in Radiology: Part 1.

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Abstract

*Machines that dream, the restless impulse for technical change that has marked radiology from its beginning and forays into deep neural networks, will no doubt unsettle long-held institu- tional practices in radiology. *A willingness to collaborate and puzzle through machine intelligence has come from those who have not accepted the status quo. A certain form of scientific curiosity has been a guiding principle in their work. *In radiology, machine intelligence has been extremely useful and built into just about every major technical innovation. But it has only been the last several years that a subfield of Al, machine learning, has begun to show remarkably fast development due to faster comput- er processing capabilities and advanced modeling and results emerging from the application of deep learning.