Open AccessA deep learning model for positioning perforated stent
Author(s) -
Erhui Wang,
Liancun Zheng
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1883/1/012157
Subject(s) - stent , artificial intelligence , window (computing) , computer vision , computer science , position (finance) , deep learning , radiology , biomedical engineering , medicine , finance , economics , operating system
How to determine the window position of the aortic stent is an important issue in cardiovascular disease research. Currently, this process is viewed in two dimensions, and a lack of information is prone to errors. Here, the real-time frame is suggested to enumerate the three-dimensional shape using the two-dimensional perspective image. A robot-assisted window-opening stent implantation with deep learning is geometrically aligned ratios in window-opening aortic endovascular repair. First, place markers during the windowed stent. Then, we located the three-dimensional pose of each stent segment. Third, the overall three-dimensional shaped stent-graft is achieved by graft gap in terpolation. It has been proposed to separate the markers from the two-dimensional fluorescence microscope for semi-automatic label detection of the image. In this way, we can better understand the opening position of the aortic stent.