3dhist08 project

Aim of the Project:

Production and market introduction of a brand-new immunohistological equipment, evaluation package and product groups that comprise reagents that support differential diagnosis, prediction, prediction of response to treatment and screening of colorectal cancer. Developing diagnostic applications for virtual microscopy to support colorectal cancer diagnosis, prediction of treatment response and peripheral blood screening.

The Óbudai University, Neumann János Faculty of Informatics, Institute of Information Systems, role of Biotech Lab

The identification of high resolution tissue images is a very complex and resource consuming process because of the size of the images and the painting properties. Recognizing the tissue components with the appropriate precision (the morphological and morphometric parameters of these components) can provide background for the automated status analysis of the examined patients. The distinguishing of the ill and healthy parts of a tissue enables more precise labelling for the scoring parameters and labelling indexes. We can apply this for the automatic diagnosis of different kinds of components (statistical index-number of nucleus, gland and epidermis detection results), that have been made detectable by various painting methods (for example: HE) and algorithms can be developed for the identification of the healthy, the inflamed, the hyperplastic and the tumorous mutation.