Within a clinical image analysis workflow with large data sets of patient images, the assessment, and review of automatically generated segmentation results by medical experts are time constrained. We present a software system able to inspect such quantitative results in a fast and intuitive way, potentially improving the daily repetitive review work of a research radiologist. Combining established standards with modern technologies creates a flexible environment to efficiently evaluate multiple segmentation algorithm outputs based on different metrics and visualizations and report these analysis results back to a clinical system environment. First experiments show that the time to review automatic segmentation results can be decreased by roughly 50% while the determination of the radiologist is enhanced.
CITATION STYLE
Stein, T., Metzger, J., Scherer, J., Isensee, F., Norajitra, T., Kleesiek, J., … Nolden, M. (2019). Efficient Web-Based Review for Automatic Segmentation of Volumetric DICOM Images. In Informatik aktuell (pp. 158–163). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-658-25326-4_33
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