Transcatheter Aortic Valve Implantation in 2017 State of the Art

The current country of approaches to analysis of medical angiographic images obtained during interventions on the circulatory system is analyzed. The main approaches — image-based algorithms, machine learning algorithms, and deep neural network learning — are considered from the point of view of individual scientific studies and from the applied point of view, i.eastward., in terms of development of visual assistance systems for medical procedures. In addition, the authors' own views on the potential for solving difficulties in creating systems for cardiovascular surgery (in particular, transcatheter replacement of the aortic valve) are presented.

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Affiliations

1. Kemerovo Country University, Kemerovo, Russian federation

   North. A. Geidarov

2. Inquiry Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russian federation

   Chiliad. Yu. Klyshnikov & E. A. Ovcharenko

Corresponding writer

Correspondence to K. Yu. Klyshnikov.

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Translated from Meditsinskaya Tekhnika, Vol. 53, No. six, Nov.-Dec., 2019, pp. fifty-55.

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Geidarov, N.A., Klyshnikov, M.Y. & Ovcharenko, E.A. Use of Neural Networks in Visual Help Systems for Transcatheter Implantation of Aortic Valve Prostheses. Biomed Eng 53, 440–446 (2020). https://doi.org/10.1007/s10527-020-09961-10

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• Received: xix June 2019

• Published: 07 March 2020

• Issue Engagement: March 2020

• DOI : https://doi.org/10.1007/s10527-020-09961-x

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Source: https://link.springer.com/article/10.1007/s10527-020-09961-x

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