Abstract
Clinical care and research increasingly rely on digitized patient information. There is a growing need to store and organize all patient data, including health records, laboratory reports, and medical images. Medical images have become indispensable for detecting and differentiating pathologies, planning interventions, and monitoring treatments. The effective retrieval of images builds on the semantic annotation of image contents and intelligent interaction with the image material. The semantic annotation of image contents has an automatic and a manual component. In our work, we heavily rely on automatic organ, tissue, and disease detection, which represents one of the main technical research questions in Medico. In this article, however, we will focus on intelligent interaction with the image material, i.e., what mobile radiology interaction and decision support systems of the future, based on automatic detectors, may look like.
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Usage of mobile applications for medical purposes might be restricted in several countries.
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A sheet-form-like internal skeletal muscle that extends across the bottom of the rib cage. The diaphragm separates the thoracic cavity (heart, lungs, and ribs) from the abdominal cavity.
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Sonntag, D., Zillner, S., Ernst, P., Schulz, C., Sintek, M., Dankerl, P. (2014). Mobile Radiology Interaction and Decision Support Systems of the Future. In: Wahlster, W., Grallert, HJ., Wess, S., Friedrich, H., Widenka, T. (eds) Towards the Internet of Services: The THESEUS Research Program. Cognitive Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-06755-1_28
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