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Scanner-specific validation of a CT simulator using a COPD-emulated anthropomorphic phantom
Author(s) -
Sachin S. Shankar,
Giavanna L. Jadick,
Eric A. Hoffman,
Jarron Atha,
Jessica C. Sieren,
Ehsan Samei,
Ehsan Abadi
Publication year - 2022
Publication title -
medical imaging 2022: physics of medical imaging
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
pISSN - 0277-786X
DOI - 10.1117/12.2613212
Subject(s) - imaging phantom , scanner , computer science , ground truth , computer vision , artificial intelligence , medical imaging , nuclear medicine , medicine
Traditional methods of quantitative analysis of CT images typically involve working with patient data, which is often expensive and limited in terms of ground truth. To counter these restrictions, quantitative assessments can instead be made through Virtual Imaging Trials (VITs) which simulate the CT imaging process. This study sought to validate DukeSim (a scanner-specific CT simulator) utilizing clinically relevant biomarkers for a customized anthropomorphic chest phantom. The physical phantom was imaged utilizing two commercial CT scanners (Siemens Somatom Force and Definition Flash) with varying imaging parameters. A computational version of the phantom was simulated utilizing DukeSim for each corresponding real acquisition. Biomarkers were computed and compared between the real and virtually acquired CT images to assess the validity of DukeSim. The simulated images closely matched the real images both qualitatively and quantitatively, with the average biomarker percent difference of 3.84% (range 0.19% to 18.27%). Results showed that DukeSim is reasonably well validated across various patient imaging conditions and scanners, which indicates the utility of DukeSim for further VIT studies where real patient data may not be feasible.

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