Targeted X-ray computed tomography: compressed sensing of stroke symptoms
AbstractThe 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.
|Publication size in sheets||0.8|
|Book||Zadrzyńska-Piętka Ewa, Badura Paweł, Kawa Jacek, Więcławek Wojciech (eds.): Information Technologies in Medicine, Advances in Intelligent Systems and Computing, vol. 471, 2016, Springer International Publishing, ISBN 978-3-319-39795-5, 518 p.|
|Keywords in English||model-based compressed sensing, algebraic iterative recon- struction, personalized computed tomography, adaptive sensing and re- covery, computerized stroke modeling, semantic image processing|
|Score|| = 15.0, 22-06-2017, BookChapterSeriesAndMatConf|
= 15.0, 22-06-2017, BookChapterSeriesAndMatConf
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