Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations

Anomaly detection for Magnetic Resonance Images (MRIs) can be solved with unsupervised methods by learning the distribution of healthy images and identifying anomalies as outliers. In presence of an additional dataset of unlabelled data containing also anomalies, the task can be framed as a semi-supervised task with negative and unlabelled sample points... (read more)

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