Abstract
The current state 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.e., 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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