Unsupervised anomaly detection with generative adversarial networks in mammography

Applied Sciences, Free Full-Text

Anomaly Detection of Breast Cancer Using Deep Learning

GitHub - Fraunhofer-AISEC/DA3D: Double-Adversarial Activation Anomaly Detection

Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms - ScienceDirect

A generative adversarial network for synthetization of regions of interest based on digital mammograms

Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms - ScienceDirect

Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms - ScienceDirect

GitHub - xtarx/Unsupervised-Anomaly-Detection-with-Generative-Adversarial- Networks: Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset

Qualitative comparison of synCTs generated by SA-GAN and

Role of General Adversarial Networks in Mammogram Analysis: A Review

Improving Supervised Outlier Detection by Unsupervised Representation Learning and Generative Adversarial Networks: An Extension of Extreme Gradient Boosting Outlier Detection by GANs

Applied Sciences, Free Full-Text

A generative adversarial network for synthetization of regions of interest based on digital mammograms

GAN for unsupervised anomaly detection on X-ray images., by Phúc Lê, Vitalify Asia

Localization of the predicted lesion on emergency brain CT images from