  Medical images can be decomposed into normal and abnormal features, which is
considered as the compositionality. Based on this idea, we propose an
encoder-decoder network to decompose a medical image into two discrete latent
codes: a normal anatomy code and an abnormal anatomy code. Using these latent
codes, we demonstrate a similarity retrieval by focusing on either normal or
abnormal features of medical images.
