Efficient Anomaly Detection with Generative Adversarial Network for Breast Ultrasound Imaging

Efficient Anomaly Detection with Generative Adversarial Network for Breast Ultrasound Imaging

We aimed to use generative adversarial network (GAN)-based anomaly detection to diagnose images of normal tissue, benign masses, or malignant masses on breast ultrasound. We retrospectively collected 531 normal breast ultrasound images from 69 patients. Data augmentation was performed and 6372 (531...

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Bibliographic Details
Main Authors: Tomoyuki Fujioka, Kazunori Kubota, Mio Mori, Yuka Kikuchi, Leona Katsuta, Mizuki Kimura, Emi Yamaga, Mio Adachi, Goshi Oda, Tsuyoshi Nakagawa, Yoshio Kitazume, Ukihide Tateishi
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Diagnostics
Subjects:
breast imaging
ultrasound
deep learning
anomaly detection
generative adversarial network
Online Access:https://www.mdpi.com/2075-4418/10/7/456

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