Method for measuring vascular diameter in coronary angiography image based on depth learning

A coronary artery and deep learning technology, applied in the computing field, can solve problems such as complex operation, unsuitability for coronary angiography, and impact on results, and achieve the effect of simple and easy operation, objective measurement results, and elimination of subjective observation errors

Inactive Publication Date: 2019-01-18
北京红云智胜科技有限公司 +1
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Problems solved by technology

[0004] Computer-aided QCA can better analyze the lesion location, stenosis degree, and involvement range, but manual participation is required in the operation process, such as manual selection of appropriate frames and pixel-level calibration of DSA images. The degree of influence, and the operation is more complicated, not suitable for coronary angiography

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  • Method for measuring vascular diameter in coronary angiography image based on depth learning
  • Method for measuring vascular diameter in coronary angiography image based on depth learning
  • Method for measuring vascular diameter in coronary angiography image based on depth learning

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Embodiment 1

[0027] Embodiment 1 of the present invention provides a method for measuring blood vessel diameter in coronary angiography images based on deep learning, which automatically calculates coronary vessel diameter and stenosis rate of stenosis without manual participation. Read the DSA (Digital subtraction angiography, digital subtraction angiography) image in coronary angiography by computer, and calculate the diameter of blood vessels in the image through image segmentation, extraction of center line, calculation of vertical line and other operations. The stenosis rate at the stenotic lesion was calculated. Generally speaking, when performing coronary angiography, doctors will perform PVA (Note: Physician Visual Assessment, physician visual assessment) on the angiographic image to judge the severity of coronary artery stenosis. A large body of data shows greater inter-observer and case-to-case variability in PVA results compared to computer-assisted methods. Compared with the P...

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Abstract

The invention discloses a method for measuring the vascular diameter in a coronary angiography image based on depth learning. The method for measuring the vascular diameter in a coronary angiography image based on depth learning comprises the following steps: a DSA image processing module converts real-time acquired DSA image data into a data stream which can be processed by a subsequent module, and stores the data stream in a memory and sends the data stream to a depth network segmentation module. The depth network segmentation module segments the acquired DSA image data to distinguish the blood vessel pixel from the background pixel. The centerline extracting module extracts the blood vessel centerline from the blood vessel pixel image. The diameter calculation module calculates the measured diameter, the reference diameter and the stenosis rate of the blood vessel based on the segmented image and the blood vessel centerline. Compared with the PVA method, the invention has more objective results and avoids the differences between different doctors and different hospitals due to different interpretation methods. This method does not need manual intervention and is easy to operate.It can be used by doctors in coronary angiography and can provide objective reference for doctors to determine the degree of coronary stenosis.

Description

technical field [0001] The invention relates to a method for measuring blood vessel diameters in coronary angiography images based on deep learning, which belongs to the technical field of computing. Background technique [0002] Coronary angiography is an important method for the diagnosis of heart diseases. Observing and analyzing the shape and movement of blood vessels and estimating the diameter of blood vessels from angiography images can assist doctors in diagnosing cardiovascular diseases and determining appropriate treatment options, which is of great clinical significance. [0003] At present, the standard method for clinical doctors to judge the degree of coronary stenosis in coronary angiography is still PVA (Physician Visual Assessment, physician visual assessment). The criteria were severe stenosis of coronary arteries with a visual lumen diameter of ≥70% or a fractional flow reserve of 0.80 or less. In the past two decades, the decision of whether to perform c...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/107G06T7/00G06T7/62
CPCA61B5/1075G06T7/0014G06T7/62
Inventor 徐波王筱斐赵森祥陈东浩叶丹
Owner 北京红云智胜科技有限公司
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