Computer-aided shape features extraction and regression models for predicting the ascending aortic a...
Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate
About this item
Full title
Author / Creator
Geronzi, Leonardo , Martinez, Antonio , Rochette, Michel , Yan, Kexin , Bel-Brunon, Aline , Haigron, Pascal , Escrig, Pierre , Tomasi, Jacques , Daniel, Morgan , Lalande, Alain , Lin, Siyu , Marin-Castrillon, Diana Marcela , Bouchot, Olivier , Porterie, Jean , Valentini, Pier Paolo and Biancolini, Marco Evangelos
Publisher
United States: Elsevier Ltd
Journal title
Language
English
Formats
Publication information
Publisher
United States: Elsevier Ltd
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Scope and Contents
Contents
AbstractObjective: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 ascending aortic aneurysm growth. Material and methods:70 patients with aneurysm, for which two 3D acquisitions were available, are included. Following segmen...
Alternative Titles
Full title
Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_hal_primary_oai_HAL_hal_04163507v1
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_hal_primary_oai_HAL_hal_04163507v1
Other Identifiers
ISSN
0010-4825
E-ISSN
1879-0534
DOI
10.1016/j.compbiomed.2023.107052
