Generative Deep Model and Unsupervised Anomaly Detection: Its Application to Medical Image Analysis

Abstract

Unsupervised anomaly detection is an important task in medical image analysis. On the other hand, there is a deep relationship between generative deep model and unsupervised anomaly detection. In this paper, firstly the generative models are described, and it is followed by an introduction of several generative deep models. Then, some topics are given in which unsupervised anomaly detection was applied to medical image analysis tasks. Finally, a newest method of self-supervised representation learning-based anomaly detection is described.