AbstractBecause of recent advances in sensor technology and a rapid increase in storage capacities, a growing number of intensity values can be recorded and associated with pixel coordinates using new imaging technologies. This growth in dimension can be observed in different scientific areas and this new category of images is referred to as multivariate images (MVIs). In these images, an almost arbitrary number of variables is associated with each pixel that represent, for instance, signal values at different time points or for different spectral bands or for different imaging parameters or modalities. Thus, these images can no longer be interpreted as gray value images or red, green, blue color images, and new information technologies are needed. In this review article, we summarize the different imaging technologies and recently published approaches to MVI mining with a special focus on biomedical applications. © 2011 John Wiley & Sons, Inc.WIREs Data Mining Knowl Discov2011 1 2‐13 DOI: 10.1002/widm.4This article is categorized under:Algorithmic Development > Biological Data MiningAlgorithmic Development > Spatial and Temporal Data MiningApplication Areas > Health CareTechnologies > Structure Discovery and Clustering