Targeted X-ray computed tomography: compressed sensing of stroke symptoms

Artur Przelaskowski


The subject of reported research is model-based compressed sensing applied to CT imaging. Personalized CT examinations were designed according to requirements of CT-based stroke diagnosis in emergency care. Adaptive sensing was optimized to recover more accurately diagnostic information which is partially hidden or overlooked in standard procedures. In addition, limited number of measurements was used to reduce radiation dose. As a result, new paradigm of integrated optimization for CT system was proposed. Formalized diagnostic model is used to improve the relevance of CT imaging in emergency diagnosis. Simulated experiments confirmed a proof of concept realization.
Author Artur Przelaskowski ZPSCiKWM
Artur Przelaskowski,,
- Department of CAD/CAM Systems Design and Computer-Aided Medicine
Book Information Technologies in Biomedicine, Advances in Intelligent Systems and Computing, vol. 471, 2016, ISBN 978-3-319-39795-5
Languageen angielski
Score (nominal)15
ScoreMinisterial score = 15.0, 22-06-2017, BookChapterSeriesAndMatConf
Ministerial score (2013-2016) = 15.0, 22-06-2017, BookChapterSeriesAndMatConf
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