We have attempted to identify potential predictors foracute and late aortic events starting from admission computed tomographic images.
D'Ancona, G., Lee, J., Pasta, S., Pilato, G., Rinaudo, A., Follis, F., et al. (2014). Computational analysis to predict false-lumen perfusion and outcome of type B aortic dissection. JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY, 148(4), 1756-1758.
Data di pubblicazione: | 2014 |
Titolo: | Computational analysis to predict false-lumen perfusion and outcome of type B aortic dissection |
Autori: | |
Citazione: | D'Ancona, G., Lee, J., Pasta, S., Pilato, G., Rinaudo, A., Follis, F., et al. (2014). Computational analysis to predict false-lumen perfusion and outcome of type B aortic dissection. JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY, 148(4), 1756-1758. |
Rivista: | |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1016/j.jtcvs.2014.06.065 |
Abstract: | We have attempted to identify potential predictors foracute and late aortic events starting from admission computed tomographic images. |
URL: | http://www.elsevier.com/inca/publications/store/6/2/3/1/5/1/index.htt |
Settore Scientifico Disciplinare: | Settore ING-IND/34 - Bioingegneria Industriale |
Appare nelle tipologie: | 1.01 Articolo in rivista |
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