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Your search keyword '"Cândea, Gabriela"' showing total 12 results
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12 results on '"Cândea, Gabriela"'

2. System Interoperability for Next Gen Services at Home. A Challenge/Opportunity for Integration

Author

Candea, Ciprian, Palumbo, Filippo, Girolami, Michele, Segato, Daniele, Candea, Gabriela Simona, Bartezzaghi, Emilio, Series Editor, Bracchi, Giampio, Series Editor, Del Bo, Adalberto, Series Editor, Sagarra Trias, Ferran, Series Editor, Stellacci, Francesco, Series Editor, Zio, Enrico, Series Editor, Andreoni, Giuseppe, editor, and Mambretti, Cinzia, editor

Published
2021
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5. Integrated Architecture for Next-Generation m-Health Services (Education, Monitoring and Prevention) in Teenagers

Author

Mazzola, Marco, Arslan, Pelin, Cândea, Gabriela, Radu, Ciprian, Azzolini, Massimiliano, Degano, Cristiana, Andreoni, Giuseppe, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Kobsa, Alfred, editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Weikum, Gerhard, editor, and Duffy, Vincent G., editor

Published
2014
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7. Study of aortic dissections treatment. Segmentation, simulation and valiadation of surgical results

Author

Bucurenciu Cristian, Costache Victor S, and Cândea Gabriela S

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

Nowadays, Computational Fluid Dynamics (CFD) it’s seen as the new trend in the management of aortic pathologies. Together with visualization capabilities of cardiovascular magnetic resonance (CMR) and computed tomography (CT) imaging, real time segmentation (volumetric) models further used as meshes in Computational Fluid Dynamic supply to the clinicians an innovative and extensive decision-making system. In the present paper, we identified and analysed the clinical indicators (lumens diameters, fenestrated area and blood volume) monitored by clinicians to evaluate the patient’ condition before and after the intervention. In order to achieve the targeted aims, we used CT scans as input data (segmented with MIMICS software) and output 3D models (3matic), further processed to mesh model in ANSYS software. Computational results validate the improved patient’ condition, meaning the blood velocity tend to have values to normal flowing conditions. As a conclusion, the linear modification of velocity can be used in further investigations as an input value of pathology treatment

Published
2019
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