A few-shot unsupervised method that combines contrastive losses on a normal-anatomy anchor bank with gradient-ascent synthetic anomalies to detect pathologies in brain MRI and chest X-rays.
In: Asian Conference on Computer Vision
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PathoSCOPE: Few-Shot Pathology Detection via Self-Supervised Contrastive Learning and Pathology-Informed Synthetic Embeddings
A few-shot unsupervised method that combines contrastive losses on a normal-anatomy anchor bank with gradient-ascent synthetic anomalies to detect pathologies in brain MRI and chest X-rays.