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Akademický článek

Deep learning methods for blood flow reconstruction in a vessel with contrast enhanced x‐ray computed tomography.

Autor: Shusong, Huang, Monica, Sigovan, Bruno, Sixou

Publikováno v: International Journal for Numerical Methods in Biomedical Engineering; Jan2024, Vol. 40 Issue 1, p1-15, 15p

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Nonlinear primal dual-method phase retrieval for X-ray in-line phase contrast imaging

Autor: Kannara Mom, Max Langer, Bruno Sixou

Publikováno v: Unconventional Optical Imaging III.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::98c179d3ed080cd1a8d5f77c1eb524df
https://doi.org/10.1117/12.2619732

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Mixed scale dense convolutional networks for x-ray phase contrast imaging

Autor: Kannara Mom, Bruno Sixou, Max Langer

Publikováno v: Applied optics
Applied optics, 2022, 61 (10), pp.2497-2505. ⟨10.1364/AO.443330⟩

International audience; X-ray in-line phase contrast imaging relies on the measurement of Fresnel diffraction intensity patterns due to the phase shift and the attenuation induced by the object. The recovery of phase and attenuation from one or sever

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::848fe43b2d4efd903757309dcb62125f
https://pubmed.ncbi.nlm.nih.gov/35471314

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Impact of the training loss in deep learning–based CT reconstruction of bone microarchitecture

Autor: Théo, Leuliet, Voichiţa, Maxim, Françoise, Peyrin, Bruno, Sixou

Publikováno v: Medical Physics
Medical Physics, 2022, 49 (5), pp.2952-2964. ⟨10.1002/mp.15577⟩

International audience; PurposeComputed tomography (CT) is a technique of choice to image bone structure at different scales. Methods to enhance the quality of degraded reconstructions obtained from low-dose CT data have shown impressive results rece

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57436ff83495486831e0d5adc8fec4e8
https://doi.org/10.1002/mp.15577

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Deep Gauss–Newton for phase retrieval

Autor: Kannara Mom, Max Langer, Bruno Sixou

Publikováno v: Optics Letters. 48:1136

We propose the deep Gauss–Newton (DGN) algorithm. The DGN allows one to take into account the knowledge of the forward model in a deep neural network by unrolling a Gauss–Newton optimization method. No regularization or step size needs to be chos

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fabb742f921755469ffc474350c80677
https://doi.org/10.1364/ol.484862

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Akademický článek

Regularization Methods for Phase Retrieval and Phase Contrast Tomography

Autor: Bruno Sixou

Publikováno v: Abstract and Applied Analysis, Vol 2015 (2015)

Phase contrast tomography is a high sensitivity medical imaging technique. Several regularization methods have been used in the literature to obtain stable solutions for the phase retrieval or the phase contrast tomography problems. Yet, the function

Externí odkaz: https://doaj.org/article/8d8a7d7301674c82a5b082451b70634e

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Nonlinear primal–dual algorithm for the phase and absorption retrieval from a single phase contrast image

Autor: Kannara Mom, Max Langer, Bruno Sixou

Publikováno v: Optics Letters. 47:5389

We propose a nonlinear primal–dual algorithm for the retrieval of phase shift and absorption from a single x ray in-line phase contrast, or Fresnel diffraction, image. The algorithm permits us to regularize phase and absorption separately. We demon

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a38e506d9bc6a6ec8cce93cfaae6ad4a
https://doi.org/10.1364/ol.469174

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Investigation of Semi-Coupled Dictionary Learning in 3-D Super Resolution HR-pQCT Imaging

Autor: Bruno Sixou, Y. Li, Françoise Peyrin, Andrew Burghard

Publikováno v: IEEE Transactions on Radiation and Plasma Medical Sciences
IEEE Transactions on Radiation and Plasma Medical Sciences, IEEE, In press, 3 (2), pp.129-136. ⟨10.1109/TRPMS.2018.2881488⟩

International audience; High Resolution peripheral Quantitative CT (HR-pQCT) permits to investigate bone micro-architecture in vivo. While it is a considerable progress over standard CT for this specific application, the spatial resolution remains so

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e472af87e3a521b89004cc734192363e
https://doi.org/10.1109/trpms.2018.2881488

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Kullback-Leibler residual and regularization for inverse problems with noisy data and noisy operator

Autor: Cyril Mory, Bruno Sixou

Publikováno v: Inverse Problems & Imaging. 13:1113-1137

We study the properties of a regularization method for inverse problems with joint Kullback-Leibler data term and regularization when the data and the operator are corrupted by some noise. We show the convergence of the method and we obtain convergen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::486f15e83a696d606b44c28d1f140eb5
https://doi.org/10.3934/ipi.2019050

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