Generative Adversarial Networks for Anomaly Detection in Biomedical Imaging: A Study on Seven Medical Image Datasets

Generative Adversarial Networks for Anomaly Detection in Biomedical Imaging: A Study on Seven Medical Image Datasets

Anomaly detection (AD) is a challenging problem in computer vision. Particularly in the field of medical imaging, AD poses even more challenges due to a number of reasons, including insufficient availability of ground truth (annotated) data. In recent years, AD models based on generative adversarial...

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Bibliographic Details
Main Authors: Marzieh Esmaeili, Amirhosein Toosi, Arash Roshanpoor, Vahid Changizi, Marjan Ghazisaeedi, Arman Rahmim, Mohammad Sabokrou
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Anomaly detection
artificial intelligence
machine learning
deep learning
unsupervised anomaly detection
generative adversarial networks
Online Access:https://ieeexplore.ieee.org/document/10043696/

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