Prikladnaya Mekhanika i Tekhnicheskaya Fizika
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS


Prikl. Mekh. Tekh. Fiz.:
Year:
Volume:
Issue:
Page:
Find




Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register

Prikladnaya Mekhanika i Tekhnicheskaya Fizika, 2022, Volume 63, Issue 4, Pages 64–72
DOI: https://doi.org/10.15372/PMTF20220407 (Mi pmtf90) 		 
Numerical optimization of geometric characteristics of vascular anastomosis using swar intelligence methods in neurosurgery

Yu. O. Kuyanovaa, A. V. Dubovoib, A. V. Bervitskiib, D. V. Parshina

a Lavrentyev Institute of Hydrodynamics of Siberian Branch of the Russian Academy of Sciences, 630090, Novosibirsk, Russia
b Federal Neurosurgical Center, 630048, Novosibirsk, Russia
Full-text PDF (370 kB) First page
References:
PDF
HTML
DOI: https://doi.org/10.15372/PMTF20220407
Abstract: Bypass surgery is widely used in the treatment of cardiovascular diseases. The problem of optimal location of cerebral vascular anastomosis is considered. An electrical circuit model of circulation of large cerebral vessels is constructed whose optimal parameters are determined numerically using swarm intelligence methods. The objective optimization function was taken to be the pressure after shunting compared with the pressure before surgery. This method was first used to solve the problem of formation of cerebral vascular anastomoses. It is shown that the obtained the results are in good agreement with the data of real surgeries.
Keywords: particle swarm method, vascular anastomosis, optimization of hemodynamic parameters.
Funding agency Grant number
Russian Science Foundation 20-71-10034
Received: 11.01.2021
Revised: 10.09.2021
Accepted: 27.09.2021
English version:
Journal of Applied Mechanics and Technical Physics, 2022, Volume 63, Issue 4, Pages 606–613
DOI: https://doi.org/10.1134/S0021894422040071
Bibliographic databases:
Document Type: Article
UDC: 51-76, 612.133
Language: Russian
Citation: Yu. O. Kuyanova, A. V. Dubovoi, A. V. Bervitskii, D. V. Parshin, “Numerical optimization of geometric characteristics of vascular anastomosis using swar intelligence methods in neurosurgery”, Prikl. Mekh. Tekh. Fiz., 63:4 (2022), 64–72; J. Appl. Mech. Tech. Phys., 63:4 (2022), 606–613
Citation in format AMSBIB
\Bibitem{KuyDubBer22}
\by Yu.~O.~Kuyanova, A.~V.~Dubovoi, A.~V.~Bervitskii, D.~V.~Parshin
\paper Numerical optimization of geometric characteristics of vascular anastomosis using swar intelligence methods in neurosurgery
\jour Prikl. Mekh. Tekh. Fiz.
\yr 2022
\vol 63
\issue 4
\pages 64--72
\mathnet{http://mi.mathnet.ru/pmtf90}
\crossref{https://doi.org/10.15372/PMTF20220407}
\elib{https://elibrary.ru/item.asp?id=49273188}
\transl
\jour J. Appl. Mech. Tech. Phys.
\yr 2022
\vol 63
\issue 4
\pages 606--613
\crossref{https://doi.org/10.1134/S0021894422040071}
Linking options:
  • https://www.mathnet.ru/eng/pmtf90
  • https://www.mathnet.ru/eng/pmtf/v63/i4/p64
    • Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Prikladnaya Mekhanika i Tekhnicheskaya Fizika Prikladnaya Mekhanika i Tekhnicheskaya Fizika
    Statistics & downloads:
    Abstract page:38
    References:14
    First page:4
     
      Contact us:
    		  Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024