Section 4: Sensor, Signal and Imaging Informatics
D. L. Rubin, S. Napel
Department of Radiology, Stanford University, Stanford, CA,USA
Imaging informatics ontologies, content based image retrieval, structured reporting
Objectives: To identify challenges and opportunities in imaging informatics that can lead to the use of images for discovery, and that can potentially improve the diagnostic accuracy of imaging professionals. Methods: Recent articles on imaging informatics and related articles from PubMed were reviewed and analyzed. Some new developments and challenges that recent research in imaging informatics will meet are identified and discussed. Results: While much literature continues to be devoted to traditional imaging informatics topics of image processing, visualization, and computerized detection, three new trends are emerging: (1) development of ontologies to describe radiology reports and images, (2) structured reporting and image annotation methods to make image semantics explicit and machine-accessible, and (3) applications that use semantic image information for decision support to improve radiologist interpretation performance. The informatics methods being developed have similarities and synergies with recent work in the biomedical informatics community that leverage large highthroughput data sets, and future research in imaging informatics will build on these advances to enable discovery by mining large image databases. Conclusions: Imaging informatics is beginning to develop and apply knowledge representation and analysis methods to image datasets. This type of work, already commonplace in biomedical research with large scale molecular and clinical datasets, will lead to new ways for computers to work with image data. The new advances hold promise for integrating imaging with the rest of the patient record as well as molecular data, for new data-driven discoveries in imaging analogous to that in bioinformatics, and for improved quality of radiology practice.