Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Diana Marcela Marin-Castrillon"'
Autor:
Leonardo Geronzi, Pascal Haigron, Antonio Martinez, Kexin Yan, Michel Rochette, Aline Bel-Brunon, Jean Porterie, Siyu Lin, Diana Marcela Marin-Castrillon, Alain Lalande, Olivier Bouchot, Morgan Daniel, Pierre Escrig, Jacques Tomasi, Pier Paolo Valentini, Marco Evangelos Biancolini
Publikováno v:
Frontiers in Physiology, Vol 14 (2023)
The current guidelines for the ascending aortic aneurysm (AsAA) treatment recommend surgery mainly according to the maximum diameter assessment. This criterion has already proven to be often inefficient in identifying patients at high risk of aneurys
Externí odkaz:
https://doaj.org/article/87dcaff65c494ca39c138661869af8be
Autor:
Leonardo Geronzi, Antonio Martinez, Michel Rochette, Kexin Yan, Aline Bel-Brunon, Pascal Haigron, Pierre Escrig, Jacques Tomasi, Morgan Daniel, Alain Lalande, Siyu Lin, Diana Marcela Marin-Castrillon, Olivier Bouchot, Jean Porterie, Pier Paolo Valentini, Marco Evangelos Biancolini
Publikováno v:
Computers in Biology and Medicine
Computers in Biology and Medicine, 2023, 162, pp.107052. ⟨10.1016/j.compbiomed.2023.107052⟩
Computers in Biology and Medicine, 2023, 162, pp.107052. ⟨10.1016/j.compbiomed.2023.107052⟩
International audience; Objective: ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to predict the ascending aortic aneurysm growth. Mat
Autor:
Pierre Fontaine, K. Gnep, Oscar Acosta, Diana Marcela Marin Castrillon, Renaud de Crevoisier, Gloria M. Díaz
Publikováno v:
19th International Conference on Bioinformatics and Bioengineering, BIBE 2019
19th International Conference on Bioinformatics and Bioengineering, BIBE 2019, Oct 2019, Athens, Greece. pp.984-988, ⟨10.1109/BIBE.2019.00183⟩
BIBE
19th International Conference on Bioinformatics and Bioengineering, BIBE 2019, Oct 2019, Athens, Greece. pp.984-988, ⟨10.1109/BIBE.2019.00183⟩
BIBE
International audience; Radiomics refers to the quantification of images by the extraction and analysis of a large number of features from different modalities, aiming to establish potential links between them and disease phenotypes. It can potential
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3c932eeb23be6b2b69f1ae66955eaf9
https://hal-univ-rennes1.archives-ouvertes.fr/hal-02472489
https://hal-univ-rennes1.archives-ouvertes.fr/hal-02472489