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Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction.
Shiraz Bhurwani, Mohammad Mahdi; Waqas, Muhammad; Podgorsak, Alexander R; Williams, Kyle A; Davies, Jason M; Snyder, Kenneth; Levy, Elad; Siddiqui, Adnan; Ionita, Ciprian N.
Afiliação
  • Shiraz Bhurwani MM; Canon Stroke and Vascular Research Center, Buffalo, New York, USA.
  • Waqas M; Biomedical Engineering, University at Buffalo - The State University of New York, Buffalo, New York, USA.
  • Podgorsak AR; Canon Stroke and Vascular Research Center, Buffalo, New York, USA.
  • Williams KA; Neurosurgery, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, USA.
  • Davies JM; Canon Stroke and Vascular Research Center, Buffalo, New York, USA.
  • Snyder K; Biomedical Engineering, University at Buffalo - The State University of New York, Buffalo, New York, USA.
  • Levy E; Canon Stroke and Vascular Research Center, Buffalo, New York, USA.
  • Siddiqui A; Biomedical Engineering, University at Buffalo - The State University of New York, Buffalo, New York, USA.
  • Ionita CN; Canon Stroke and Vascular Research Center, Buffalo, New York, USA.
J Neurointerv Surg ; 12(7): 714-719, 2020 Jul.
Article em En | MEDLINE | ID: mdl-31822594
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Angiografia Digital / Aneurisma Intracraniano / Aprendizado Profundo Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Angiografia Digital / Aneurisma Intracraniano / Aprendizado Profundo Idioma: En Ano de publicação: 2020 Tipo de documento: Article