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Simulation based evaluation framework for deep learning unsupervised anomaly detection on brain FDG-PET

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Simulation based evaluation framework for deep learning unsupervised anomaly detection on brain FDG-PET

Unsupervised anomaly detection using deep learning models is a popular computer-aided diagnosis approach because it does not need annotated data and is not restricted to the diagnosis of a disease seen during training. Such approach consists in first learning the distribution of anomaly free images. Images presenting anomalies are then detected ...

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