Modeling and interpretation of physiopathological processes using cellular and histopathological images

Nowadays, cellular imaging plays an essential role in detection and diagnosis of several diseases, ranging from functional information to molecular expressions. Numerous complex system metabolic and functional studies require the support of histological or immunohistochemistry images, which are characterized by their large dimensions and the presence of a high number of cells, which limits the ability of operators to see the “big picture” of the imaged tissue. In addition, visual inspection of microscopy images is often time-consuming, highly subjective and requires experienced operators. Our research group covers the development of automated strategies for the segmentation and the classification of cellular structures within medical images. The morphological/antigenic characterization of cells within 2D/3D contexts and the combination of biological tools with advanced image processing techniques allows to obtain an integrated representation of cells interactions, even in niche-like environments. During the last years, our research group also has acquired the know-how for the extraction of quantitative data from histopathological images to discover new prognostic and predictive biomarkers in cancer development.

ERC Sector:

  • LS7_1 Medical engineering and technology
  • LS4_6 Cancer and its biological basis
  • LS2_14 Biological systems analysis, modelling and simulation

Keywords:

  • Biomedical imaging, machine intelligence
  • Histopathology
  • Segmentation

Research groups