Intelligent Imaging: Anatomy of Machine Learning and Deep Learning

• Published in: Journal of nuclear medicine technology Vol. 47; no. 4; pp. 273 - 281
• Main Author: Currie, Geoff
• Format: Journal Article
• Language: English
• Published: United States 01-12-2019
• Subjects: Deep Learning; Diagnostic Imaging; Image Processing, Computer-Assisted; Nuclear Medicine; artificial neural network; deep learning; nuclear medicine; convolutional neural network; artificial intelligence
• ISSN: 0091-4916; 1535-5675
• DOI: 10.2967/jnmt.119.232470

The emergence of artificial intelligence (AI) in nuclear medicine and radiology has been accompanied by AI commentators and experts predicting that AI would make radiologists, in particular, extinct. More realistic perspectives suggest significant changes will occur in medical practice. There is no escaping the disruptive technology associated with AI, neural networks, and deep learning, the most significant perhaps since the early days of Roentgen, Becquerel, and Curie. AI is an omen, but it need not be foreshadowing a negative event; rather, it is heralding great opportunity. The key to sustainability lies not in resisting AI but in having a deep understanding and exploiting the capabilities of AI in nuclear medicine while mastering those capabilities unique to the human resources.