Abstract
Object detection, as one of the most fundamental and challenging problems in computer vision, has attracted much attention in recent years. Over the past two decades, we have witnessed the rapid technological evolution of object detection and its profound impact on the whole field of computer vision. In this paper, aortography key point detection approaches for transcatheter aortic valve implantation based on machine learning tools are discussed. The paper provides a description and analytical comparison of such popular methods as "object detection", "pose estimation". As a result of this study, a visual assessment system is proposed to facilitate the performance of the intervention procedure. The final accuracy of the proposed system reaches 79.3% with an analysis speed of 12 ms per image.
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