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3D Automatic Segmentation of Aortic Computed Tomography Angiography Combining Multi-View 2D Convolutional Neural Networks.
Fantazzini, Alice; Esposito, Mario; Finotello, Alice; Auricchio, Ferdinando; Pane, Bianca; Basso, Curzio; Spinella, Giovanni; Conti, Michele.
Affiliation
  • Fantazzini A; Department of Experimental Medicine, University of Genoa, Via Leon Battista Alberti, 2, 16132, Genoa, Italy. alice.fantazzini@edu.unige.it.
  • Esposito M; Camelot Biomedical Systems S.r.l, Via Al Ponte Reale, 2, 16124, Genoa, Italy. alice.fantazzini@edu.unige.it.
  • Finotello A; Camelot Biomedical Systems S.r.l, Via Al Ponte Reale, 2, 16124, Genoa, Italy.
  • Auricchio F; Department of Integrated Surgical and Diagnostic Sciences, University of Genoa, Genoa, Italy.
  • Pane B; Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy.
  • Basso C; Vascular and Endovascular Surgery Unit, IRCCS Ospedale Policlinico San Martino, University of Genoa, Genoa, Italy.
  • Spinella G; Camelot Biomedical Systems S.r.l, Via Al Ponte Reale, 2, 16124, Genoa, Italy.
  • Conti M; Vascular and Endovascular Surgery Unit, IRCCS Ospedale Policlinico San Martino, University of Genoa, Genoa, Italy.
Cardiovasc Eng Technol ; 11(5): 576-586, 2020 10.
Article in En | MEDLINE | ID: mdl-32783134
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Aorta, Abdominal / Aortography / Radiographic Image Interpretation, Computer-Assisted / Aortic Aneurysm, Abdominal / Imaging, Three-Dimensional / Computed Tomography Angiography / Deep Learning Type of study: Observational_studies / Risk_factors_studies Limits: Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Cardiovasc Eng Technol Year: 2020 Document type: Article Affiliation country: Italy Country of publication: United States
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Aorta, Abdominal / Aortography / Radiographic Image Interpretation, Computer-Assisted / Aortic Aneurysm, Abdominal / Imaging, Three-Dimensional / Computed Tomography Angiography / Deep Learning Type of study: Observational_studies / Risk_factors_studies Limits: Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Cardiovasc Eng Technol Year: 2020 Document type: Article Affiliation country: Italy Country of publication: United States