Medical imaging (MI) is at the heart of many of today’s improved diagnostic and treatment technologies. Computer-based solutions are vastly more capable of both quantitative measurement of the medical condition and the pre-processing tasks of filtering, sharpening, and focusing image detail. Bio-inspired and Soft Computing (BC, SC) techniques have been successfully applied in each of the fundamental steps of medical image processing and analysis (e.g. restoration, segmentation, registration or tracking). The natural partnership of humans and intelligent systems and machines in MI is to provide the clinician with powerful tools to take better decisions regarding diagnostic and treatment. The main goal of the network is to create a training programme where the enrolled early-stage researchers (ESRs) will be exposed to a wide variety of SC and BC techniques, as well as to the challenge of applying them to different situations and problems within the different MI stages. A personalised, exhaustive and complementary programme will consist of: i) a personalised research plan based on individual research projects; ii) local and network-wide specific training courses, both in face-to-face and virtual modalities; iii) the network’s complementary skills courses, workshops and final conference; and iv) the international research stays among the different partners. The collaboration of experts from the area of MI with those working on BC and SC applications to computer vision will generate new and viable methods and solutions from the combined ideas of these communities. The presence of both research and technical partners in the network, including hospitals and companies, will provide the appropriate framework for application domain focused research. The trained ESRs will acquire a strong background for the development of intelligent systems based on BC-SC providing flexible application-oriented solutions to current MI problems in the clinical and research field.
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