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 (FMIS / DCSDCAM)
Artur Przelaskowski,,
- Department of CAD/CAM Systems Design and Computer-Aided Medicine
Publication size in sheets0.8
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 Englishmodel-based compressed sensing, algebraic iterative recon- struction, personalized computed tomography, adaptive sensing and re- covery, computerized stroke modeling, semantic image processing
Languageen angielski
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 15.0, 30-01-2020, BookChapterSeriesAndMatConfByConferenceseries
Ministerial score (2013-2016) = 15.0, 30-01-2020, BookChapterSeriesAndMatConfByConferenceseries
Publication indicators WoS Citations = 0; Scopus Citations = 0
Citation count*
Share Share

Get link to the record

* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Are you sure?