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Benjamin M. W. Tsui
Researcher at Johns Hopkins University
Publications - 437
Citations - 16230
Benjamin M. W. Tsui is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Iterative reconstruction & Imaging phantom. The author has an hindex of 65, co-authored 435 publications receiving 15346 citations. Previous affiliations of Benjamin M. W. Tsui include University of Nicosia & University of Chicago.
Papers
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Journal ArticleDOI
4D XCAT phantom for multimodality imaging research
TL;DR: The XCAT provides an important tool in imaging research to evaluate and improve imaging devices and techniques and may also provide the necessary foundation with which to optimize clinical CT applications in terms of image quality versus radiation dose.
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Dynamic Imaging of Allogeneic Mesenchymal Stem Cells Trafficking to Myocardial Infarction
Dara L. Kraitchman,Mitsuaki Tatsumi,Wesley D. Gilson,Takayoshi Ishimori,Dorota A. Kedziorek,Piotr Walczak,W. Paul Segars,Hunter H. Chen,Danielle Fritzges,Izlem Izbudak,Randell G. Young,Michelle Marcelino,Mark F. Pittenger,Meiyappan Solaiyappan,Raymond C. Boston,Benjamin M. W. Tsui,Richard L. Wahl,Jeff W.M. Bulte +17 more
TL;DR: Noninvasive radionuclide imaging is well suited to dynamically track the biodistribution and trafficking of mesenchymal stem cells to both target and nontarget organs.
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Development of a 4-D digital mouse phantom for molecular imaging research.
TL;DR: The phantom is capable of producing realistic molecular imaging data from which imaging devices and techniques can be evaluated and can be used in the development of new imaging instrumentation, image acquisition strategies, and image processing and reconstruction methods.
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Realistic CT simulation using the 4D XCAT phantom
TL;DR: The authors develop a unique CT simulation tool based on the 4D extended cardiac-torso (XCAT) phantom, a whole-body computer model of the human anatomy and physiology based on NURBS surfaces that offers vast improvement in terms of realism and the ability to generate 3D and 4D data from anatomically diverse patients.
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Noise properties of the EM algorithm: I. Theory.
TL;DR: The theory of expectation-maximization can be used as a basis for calculation of objective figures of merit for image quality over a wide range of conditions in emission tomography.