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.