An image-based framework for intellectual decision making in medical research

Medical decisional problems strongly rely on the analysis and interpretation of diagnostic images acquired by different investigation techniques. Information extraction and correlation from these are usually demanding tasks that can burden the routine work of clinicians. In this paper, an image-based framework is presented which is devoted to the automated extraction of knowledge and data from biomedical images used for intellectual decision making in clinical and medical research. An ontological approach is adopted for encoding different kind of knowledge required in problem solving. Modeling the pre-clinical stage of Parkinson's disease is presented as eligible case study.