The qualitative analysis of histopathological images is a time-consuming process and is subject to inter- and intra-reader variations. This affects the prediction of the clinical outcome in an undesirable way. As a result, we are developing image analysis systems for computer-assisted interpretations of these images to assist pathologists in their decision making. Our goal is to provide computational tools with which they can extract quantitative features useful for more objective and accurate diagnosis and prognosis. Furthermore, we are investigating high-performance computational infrastructures to efficiently process these large images. The developed systems provide promising results, both in terms of accuracy and computational efficiency.