Deep network segmentation method for coronary artery lumen contour under OCT image
A coronary artery and deep network technology, applied in image analysis, neural learning methods, biological neural network models, etc., can solve problems such as low positioning accuracy, inability to obtain good segmentation results, and unclosed contours, and achieve the effect of accelerating efficiency
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[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0032] In this embodiment, a deep network segmentation algorithm for the contour of the coronary artery lumen under the OCT image provided by the present invention is used to segment the inner wall of the lumen in the OCT image, such as Figure 5 shown, including the following specific steps:
[0033] S101. Acquire a scanning sequence of coronary artery OCT image slices, construct a coronary artery data set under the OCT image; then use labeling ...
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