Abstract: Imaging is a critical and indispensable component of modern healthcare. The automated analysis of medical images has a vast range of applications in evidenced-based diagnosis, physician education, and biomedical research. These decision support applications are predicated on the ability to objectively compute the similarity of image content in a manner that matches the subjective similarity judgement of human domain experts. In this talk, I will present my work within this field, describing methods for characterising and comparing the visual content of images, including a graph-based method for comparing 3D PET-CT lung cancer images and my more recent work using convolutional neural networks.