Automatically hemodynamic analysis of AAA from CT images based on deep learning and CFD approaches

Y. V. Fedotova, R. U.I. Epifanov, A. A. Karpenko, R. I. Mullyadzhanov

Research output: Contribution to journalConference articlepeer-review

Abstract

Abdominal aortic aneurysm is a serious disease which course is accompanied by the development of health complications and often leads to patient death due to aortic rupture. One of the powerful methods to estimate the risk of rupture is three-dimensional patient-specific hemodynamic analysis. In this study, we develop a software tool based on deep learning and CFD methods to perform automated computational hemodynamics with patient-specific geometry reconstructed from computed tomography images.

Original languageEnglish
Article number012069
JournalJournal of Physics: Conference Series
Volume2119
Issue number1
DOIs
Publication statusPublished - 15 Dec 2021
Event37th Siberian Thermophysical Seminar, STS 2021 - Novosibirsk, Russian Federation
Duration: 14 Sep 202116 Sep 2021

OECD FOS+WOS

  • 1.03 PHYSICAL SCIENCES AND ASTRONOMY

Fingerprint

Dive into the research topics of 'Automatically hemodynamic analysis of AAA from CT images based on deep learning and CFD approaches'. Together they form a unique fingerprint.

Cite this