Artificial Intelligence in Diagnostic Imaging

Abstract

Among all artificial intelligence (AI) techniques and methods, machine learning (ML) includes all those approaches that allow computers to learn from data without being explicitly programmed. ML has been extensively applied to medical imaging, and the last few years have seen the rise of deep learning (DL), which is an area of ML focused on the application and training of artificial neural networks with a very large number of layers, also called deep neural networks. This chapter aims to provide some insights into AI, including basic knowledge on ML and DL algorithms, challenges, and future directions. It provides some examples of AI applications in diagnostic imaging. Successful application of DL techniques in a healthcare setting poses a set of challenges that have to be carefully considered due to the particular context. The main challenges and the most promising open directions to deal with them are: labeling and annotations, overfitting, and privacy and ethical issues.

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