Machine Learning Applications for Head and Neck Imaging

Abstract

The head and neck (HN) consists of a large number of vital anatomic structures within a compact area. Imaging plays a central role in the diagnosis and management of major disorders affecting the HN. This article reviews the recent applications of machine learning (ML) in HN imaging with a focus on deep learning approaches. It categorizes ML applications in HN imaging into deep learning and traditional ML applications and provides examples of each category. It also discusses the main challenges facing the successful deployment of ML-based applications in the clinical setting and provides suggestions for addressing these challenges.

Keywords: Artificial intelligence; Autosegmentation; Classification; Convolutional neural network; Deep learning; Head and neck cancer; Head and neck imaging; Machine learning.