Target detection in latent space

A medical image system, comprising:

• a non-transitory, machine readable storage medium storing program instructions and medical image data;
• and
• a programmed processor coupled to the storage medium and configured by the program instructions for:
• input of medical image data to a variational autoencoder configured to reduce a dimensionality of the medical image data to a latent space having one or more latent variables with latent variable values as an encoder, such that the latent variable values corresponding to an image with no tissue of a target type fit within one or more clusters of the values of the latent variables, the variational autoencoder having been trained with the encoder and a decoder configured to regenerate images from the training values of the latent variables output by the encoder;
• detection of whether the latent variable values corresponding to the medical image data fit within the one or more clusters of latent variable values of training image data for the variational autoencoder, the fit determined from the latent variable values for the medical image output by the encoder relative to the clusters of the latent variable values of the training image data for the variational autoencoder;
• and
• determination that a tissue abnormality is present in response to a determination that the medical image data have less than a threshold probability of fitting within any of the one or more clusters.