Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Alexandre Bône"'
Autor:
Bleuenn Brusset, Marion Jacquemin, Yann Teyssier, Gaël S. Roth, Nathalie Sturm, Matthieu Roustit, Alexandre Bône, Julien Ghelfi, Charlotte E. Costentin, Thomas Decaens
Publikováno v:
JHEP Reports, Vol 6, Iss 1, Pp 100957- (2024)
Background & Aims: The diagnosis of hepatocellular carcinoma (HCC) in patients with cirrhosis relies on non-invasive criteria based on international guidelines. The advent of systemic therapies warrants reconsideration of the role of biopsy specimens
Externí odkaz:
https://doaj.org/article/2482d8486980414b86aebc19cd4b1c2b
Autor:
Igor Koval, Alexandre Bône, Maxime Louis, Thomas Lartigue, Simona Bottani, Arnaud Marcoux, Jorge Samper-González, Ninon Burgos, Benjamin Charlier, Anne Bertrand, Stéphane Epelbaum, Olivier Colliot, Stéphanie Allassonnière, Stanley Durrleman
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-16 (2021)
Abstract Alzheimer’s disease (AD) is characterized by the progressive alterations seen in brain images which give rise to the onset of various sets of symptoms. The variability in the dynamics of changes in both brain images and cognitive impairmen
Externí odkaz:
https://doaj.org/article/3bb22a9b97884f2c9673b8a79351bb74
Autor:
Alexandre Bône, Samy Ammari, Yves Menu, Corinne Balleyguier, Eric Moulton, Émilie Chouzenoux, Andreas Volk, Gabriel C.T.E. Garcia, François Nicolas, Philippe Robert, Marc-Michel Rohé, Nathalie Lassau
Publikováno v:
Investigative Radiology. 57:527-535
The aim of this study was to evaluate a deep learning method designed to increase the contrast-to-noise ratio in contrast-enhanced gradient echo T1-weighted brain magnetic resonance imaging (MRI) acquisitions. The processed images are quantitatively
Autor:
Omar Ali, Alexandre Bône, Caterina Accardo, Omar Belkouchi, Marc-Michel Rohe, Eric Vibert, Irene Vignon-Clementel
Publikováno v:
Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery
Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery, LNCS-13602, Springer Nature Switzerland, pp.125-133, 2022, Lecture Notes in Computer Science, ⟨10.1007/978-3-031-19660-7_12⟩
Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery ISBN: 9783031196591
Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery, LNCS-13602, Springer Nature Switzerland, pp.125-133, 2022, Lecture Notes in Computer Science, ⟨10.1007/978-3-031-19660-7_12⟩
Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery ISBN: 9783031196591
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e70f65847f7d0a280a4fe52edc6a3b6e
https://hal.science/hal-03919572/file/omarali_0009_miccai_cameraready.pdf
https://hal.science/hal-03919572/file/omarali_0009_miccai_cameraready.pdf
Autor:
Walfrido Moraes Tomas, Rodrigo Baggio, Christian Niel Berlinck, André Restel Camilo, Cátia Nunes da Cunha, Geraldo Damasceno-Junior, Giselda Durigan, Rodrigo Dutra-Silva, Alessandra Fidélis, Letícia Couto Garcia, Heitor Miraglia Herrera, Renata Libonati, José Antonio Marengo, Maxwell da Rosa Oliveira, Gerhard Ernst Overbeck, Alexandre de Matos Martins Pereira, Valério De Patta Pillar, Vânia Regina Pivello, Danilo Bandini Ribeiro, José Felipe Ribeiro, Alexandre Bonesso Sampaio, Antonio dos Santos Júnior, Isabel Belloni Schmidt, Balbina Maria Araújo Soriano, Liliani Marília Tiepolo, Thiago Philipe de Camargo e Timo, Cátia Urbanetz, Daniel Luis Mascia Vieira, Bruno Machado Teles Walter
Publikováno v:
Pesquisa Agropecuária Brasileira, Vol 59 (2024)
Abstract Legal reserve areas (LRAs) are a fundamental part of the Brazilian conservation strategy, together with permanent preservation areas. The LRAs are intended to maintain biodiversity and can be managed sustainably. When these areas are home to
Externí odkaz:
https://doaj.org/article/19236e1234cf42d39ef029621e097b49
Publikováno v:
International Journal of Computer Vision
International Journal of Computer Vision, Springer Verlag, 2020, 128, pp.2873-2896. ⟨10.1007/s11263-020-01343-w⟩
International Journal of Computer Vision, 2020, 128, pp.2873-2896. ⟨10.1007/s11263-020-01343-w⟩
International Journal of Computer Vision, Springer Verlag, 2020, ⟨10.1007/s11263-020-01343-w⟩
International Journal of Computer Vision, Springer Verlag, 2020, 128, pp.2873-2896. ⟨10.1007/s11263-020-01343-w⟩
International Journal of Computer Vision, 2020, 128, pp.2873-2896. ⟨10.1007/s11263-020-01343-w⟩
International Journal of Computer Vision, Springer Verlag, 2020, ⟨10.1007/s11263-020-01343-w⟩
International audience; In this paper, we propose a generative statistical model to learn the spatiotemporal variability in longitudinal shape data sets, which contain repeated observations of a set of objects or individuals over time. From all the s
Autor:
Rebeca Vétil, Clément Abi-Nader, Alexandre Bône, Marie-Pierre Vullierme, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031164330
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a275ef53c489699f7ef68b33d14792a
https://doi.org/10.1007/978-3-031-16434-7_45
https://doi.org/10.1007/978-3-031-16434-7_45
Autor:
Andreas Volk, Emilie Chouzenoux, François Bidault, Samy Ammari, Francois Nicolas, Yves Menu, Alexandre Bône, Nathalie Lassau, Philippe Robert, Eric Moulton, Marc-Michel Rohe, Corinne Balleyguier
Publikováno v:
Investigative radiology. 57(2)
This study proposes and evaluates a deep learning method that predicts surrogate images for contrast-enhanced T1 from multiparametric magnetic resonance imaging (MRI) acquired using only a quarter of the standard 0.1 mmol/kg dose of gadolinium-based
Autor:
Froso Sophocleous, Alexandre Bône, Andrew I.U. Shearn, Mari Nieves Velasco Forte, Jan L. Bruse, Massimo Caputo, Giovanni Biglino
Publikováno v:
Sophocleous, F, Bone, A, Shearn, A I U, Velasco Forte, M N, Bruse, J L, Caputo, M & Biglino, G 2022, ' Feasibility of a longitudinal statistical atlas model to study aortic growth in congenital heart disease ', Computers in Biology and Medicine, vol. 144, no. 105326, 105326 . https://doi.org/10.1016/j.compbiomed.2022.105326
Background Studying anatomical shape progression over time is of utmost importance to refine our understanding of clinically relevant processes. These include vascular remodelling, such as aortic dilation, which is particularly important in some cong
Autor:
Philippe Robert, Samy Ammari, Francois Nicolas, Alexandre Bône, Nathalie Lassau, Jean-Philippe Lamarque, Corinne Balleyguier, Mickael Elhaik, Marc-Michel Rohe, Emilie Chouzenoux
Publikováno v:
ISBI
Proceedings ISBI 2021
ISBI 2021-International Symposium on Biomedical Imaging
ISBI 2021-International Symposium on Biomedical Imaging, Apr 2021, Nice / Virtual, France
Proceedings ISBI 2021
ISBI 2021-International Symposium on Biomedical Imaging
ISBI 2021-International Symposium on Biomedical Imaging, Apr 2021, Nice / Virtual, France
International audience; Contrast-enhanced medical images offer vital insights for the accurate diagnosis, characterization and treatment of tumors, and are routinely used worldwide. Acquiring such images requires to inject the patient intravenously w