Zobrazeno 1 - 10
of 191
pro vyhledávání: '"Frédéric Noo"'
Publikováno v:
Medical Imaging 2023: Physics of Medical Imaging.
Autor:
Viktor, Haase, Katharina, Hahn, Harald, Schöndube, Karl, Stierstorfer, Andreas, Maier, Frédéric, Noo
Publikováno v:
Medical Physics. 49:5014-5037
Background Various clinical studies show the potential for a wider quantitative role of diagnostic X‐ray computed tomography (CT) beyond size measurements. Currently, the clinical use of attenuation values is, however, limited due to their lack of
Publikováno v:
7th International Conference on Image Formation in X-Ray Computed Tomography.
Publikováno v:
Medical Imaging 2022: Physics of Medical Imaging.
Autor:
Jingyan Xu, Frédéric Noo
Publikováno v:
IEEE Trans Med Imaging
Joint image reconstruction for multiphase CT can potentially improve image quality and reduce dose by leveraging the shared information among the phases. Multiphase CT scans are acquired sequentially. Inter-scan patient breathing causes small organ s
Autor:
Frédéric Noo, Rolf Clackdoyle
Publikováno v:
IEEE Transactions on Radiation and Plasma Medical Sciences
IEEE Transactions on Radiation and Plasma Medical Sciences, IEEE, In press, pp.1-1. ⟨10.1109/TRPMS.2019.2918222⟩
IEEE Trans Radiat Plasma Med Sci
IEEE Transactions on Radiation and Plasma Medical Sciences, IEEE, In press, pp.1-1. ⟨10.1109/TRPMS.2019.2918222⟩
IEEE Trans Radiat Plasma Med Sci
International audience; For situations of cone-beam scanning where the measurements are incomplete, we propose a method to quantify the severity of the missing information at each voxel. This incompleteness metric is geometric; it uses only the relat
Autor:
Jingyan Xu, Frédéric Noo
Publikováno v:
Phys Med Biol
We propose a hyperparameter learning framework that learns patient-specific hyperparameters for optimization based image reconstruction problems for x-ray CT applications. The framework consists of two functional modules: (1) a hyperparameter learnin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::216cc4e36483b841992fc8362b547da8
https://europepmc.org/articles/PMC8584383/
https://europepmc.org/articles/PMC8584383/
Autor:
Andreas Maier, Frédéric Noo, Harald Schöndube, Viktor Haase, Karl Stierstorfer, Katharina Hahn
Publikováno v:
Medical Imaging 2021: Physics of Medical Imaging.
Since the introduction of model-based iterative reconstruction for computed tomography (CT) by Thibault et al. in 2007, statistical weights play an important role in the problem formulation with the objective to improve image quality. Statistical wei
Autor:
Viktor Haase, Karl Stierstorfer, Harald Schöndube, Frédéric Noo, Andreas Maier, Katharina Hahn
Publikováno v:
2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).
Material decomposition algorithms for dual energy CT require knowledge on the energy response of the used system. This knowledge can be gained either through calibration measurements or using an explicit analytical model. While the former approach is
Autor:
Frédéric Noo, Jingyan Xu
Publikováno v:
Physics in Medicine & Biology. 67:07TR01
The past decade has seen the rapid growth of model based image reconstruction (MBIR) algorithms, which are often applications or adaptations of convex optimization algorithms from the optimization community. We review some state-of-the-art algorithms