Summary
Computed understanding of CT brain images used for assisted diagnosis of acute ischemic stroke disease was the subject of reported study. Stroke slicer was proposed as computer aided diagnosis (CAD) tool that allows extraction and enhancement of direct early ischemia sign - subtle hypodense of local tissue damage. Hypoattenuation of selected CT scan areas was visualized distinctly in a form of semantic maps. Moreover, brain tissue texture was characterized, analyzed and classified in multiscale domain to detect the areas of ischemic events. As the results of slice-oriented processing, the automatically indicated regions of ischemia and enhanced hypodensity maps were proposed as additional view for computerized assisted diagnosis. The experimental verification of stroke slicer was concentrated on diagnostic improvement in clinical practice by using semantic maps as additional information for interpretation procedure. Reported results indicate possible improvement of diagnostic output for really challenging problem of as early as possible CT-based ischemic stroke detection.
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Przelaskowski, A., Ostrek, G., Sklinda, K., Walecki, J., Jóźwiak, R. (2009). Stroke Slicer for CT-Based Automatic Detection of Acute Ischemia. In: Kurzynski, M., Wozniak, M. (eds) Computer Recognition Systems 3. Advances in Intelligent and Soft Computing, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93905-4_53
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DOI: https://doi.org/10.1007/978-3-540-93905-4_53
Publisher Name: Springer, Berlin, Heidelberg
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