Abstract: Systems and methods are provided for generating clusters of anomalous images. Histopathological samples are images at an associated imaging system to produce a plurality of images. A plurality of anomalous images are identified from the plurality of images at an anomaly detection system, having an associated latent space. The plurality of anomalous images are clustered to generate a plurality of clusters within a feature space defined by a set of classification features. The set of classification features include a feature derived from the latent space associated with the anomaly detection system.

Abstract: Systems and methods are provided for screening histopathology tissue samples. An anomaly detection system is trained on a plurality of training images. Each of the plurality of training images represents a tissue sample that is substantially free of abnormalities. A test image, representing a tissue sample, is provided to the anomaly detection system. A deviation from normal score is generated for at least a portion of the test image. The deviation from normal score represents a degree of abnormality in the tissue sample represented by the test image.