1) Review the year's most significant advances in imaging informatics. 2) Understand current directions in biomedical informatics research of importance to radiology, including ontologies, data mining, natural language processing, reporting systems, and decision support. 3) Describe recent advances in image processing and analysis, and their applications in radiology, including image reconstruction, filtering and post-processing, pattern recognition, computer-aided detection and diagnosis, and visualization.
ABSTRACTThe field of imaging informatics is rapidly advancing in its ability to address challenges related to clinical big data and harnessing this information for precision medicine. In the past year, the field has experienced growth in a variety of areas including radiomics (the generation of high dimensional features from images), development of new ontologies and standards for capturing information from images and reports, and unsupervised learning from images to predict the course of a disease and treatment response. In addition, we have seen a remarkable growth in novel approaches that go beyond pixel data by integrating imaging with other biomedical data, standardizing imaging workflows, and improving the quality and utility of image-derived information in clinical practice. This session, developed in partnership with the American Medical Informatics Association (AMIA) and the Society of Imaging Informatics in Medicine (SIIM), highlights the year's most important advances in imaging informatics. This course provides a comprehensive "Year in Review" of informatics in medical imaging.
URLhttp://www.rsna.org/Informatics/2016/