Images are used extensively nowadays. With the digital revolution, we easily generate, send, and observe images, all at a very low cost. Images are also used extensively in biological research and in the medical clinic. Biological images are studied mainly in basic science research, mostly at the cellular and molecular level. Medical images are used for clinical purposes, and focus on the tissue and organ level. Both kinds of images are often complicated and heterogeneous, and analyzing them requires sophisticated computational techniques. The goal of these techniques is to extract meaningful knowledge about the image content. For example, the automated identification of objects in the image (such as cells, intracellular components, or a cancer tumor), tracking cells, organelles, or cancer cells in consecutive video frames, or phenotype identification by object properties (size, light intensity, shape, etc.). Images also require large volumes of storage, raising the need for efficient compression algorithms, in order to store them.