Open AccessMedicineComputer Science

G. Currie, K. Hawk, E. Rohren, Alanna Vial, R. Klein

2019.10.7Journal of Medical Imaging and Radiation Sciences

DOI: 10.1016/j.jmir.2019.09.005

tlooto Summary

An understanding of the principles and application of radiomics, artificial neural networks, machine learning, and deep learning is an essential foundation to weave design solutions that accommodate ethical and regulatory requirements, and to craft AI-based algorithms that enhance outcomes, quality, and efficiency.

Abstract

Artificial intelligence (AI) in medical imaging is a potentially disruptive technology. An understanding of the principles and application of radiomics, artificial neural networks, machine learning, and deep learning is an essential foundation to weave design solutions that accommodate ethical and regulatory requirements, and to craft AI-based algorithms that enhance outcomes, quality, and efficiency. Moreover, a more holistic perspective of applications, opportunities, and challenges from a programmatic perspective contributes to ethical and sustainable implementation of AI solutions.

Citation format

CURRIE, G., et al. Machine learning and deep learning in medical imaging: Intelligent imaging. Journal of Medical Imaging and Radiation Sciences, 2019.