Coastal image interpretation using background knowledge and semantics

Coastal image interpretation using background knowledge and semantics

In this article, we present a framework to model and to use knowledge provided by experts for remote sensing image interpretation of coastal area. The goal of this approach is to associate semantic to regions issued from the segmentation of an image. The idea is to start with a raw description of the knowledge given by the expert on the different thematic object classes present in the image. Th...

On the interplay of machine learning and background knowledge in image interpretation by Bayesian networks

OBJECTIVES To obtain a balanced view on the role and place of expert knowledge and learning methods in building Bayesian networks for medical image interpretation. METHODS AND MATERIALS The interpretation of mammograms was selected as the example medical image interpretation problem. Medical image interpretation has its own common standards and procedures. The impact of these on two complemen...

Background Knowledge and Translation Ability

Critiquing Knowledge Representation in Medical Image Interpretation Using Structure Learning

Medical image interpretation is a difficult problem for which human interpreters, radiologists in this case, are normally better equipped than computers. However, there are many clinical situations where radiologist’s performance is suboptimal, yielding a need for exploitation of computer-based interpretation for assistance. A typical example of such a problem is the interpretation of mammogram...

Cognitive Approach to Medical Image Semantics Description and Interpretation

In the paper will be presented new achievements of the authors obtained in the field of development some new cognitive information systems, performed the tasks of automatic understanding of medical image semantics. Such systems are dedicated to implementation of the machine semantics understanding paradigm for selected image types, with special regards to various medical visualization. The prac...