Intelligent Automated Negotiation for Medical Image Segmentation Failure using Multi-Agent Systems

International audienceImage segmentation errors can be fatal in the medical field. Sometimes even automated segmentation methods fail, they can be affected by poor image quality, artifacts or even unexpected noises. A practical task such as the segmentation of medical images is highly required for decision-making either for diagnosis or for the treatment of the patient. In this paper, we present a method based on negotiation strategies, of multi-agent systems, for the detection and correction of segmentation failures. The main advantages of our method are: 1) support for a fast negotiation strategy on a 2D view of each slice of the 3D image; 2) our approach is independent of the initial segmentation method; 3) The method is applicable to a variety of medical structures