Parameter calculation method, system, readable storage medium and computer device
A parameter calculation and parameter technology, applied in the field of medical image analysis, can solve problems such as large calculation method errors, achieve the effects of reducing errors, improving accuracy and versatility
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Embodiment 1
[0051] see figure 1 , shows the parameter calculation method in the first embodiment of the present invention, which is used to calculate the hemodynamic parameters of blood vessels, the blood vessels include coronary arteries and aorta, and the method includes steps S01 to S06.
[0052] In step S01 , the blood vessel image is processed to obtain pixel-based preliminary segmentation of the aorta and coronary artery respectively.
[0053] Specifically, the vascular images include but not limited to vascular CT (Computed Tomography, computerized tomography) images and vascular MRI (MRI, Magnetic Resonance Imaging, nuclear magnetic resonance) images, and the like.
[0054] Among them, processing the blood vessel image refers to performing a blood vessel segmentation algorithm on the blood vessel image. The blood vessel segmentation algorithm refers to "extracting" blood vessels from the blood vessel image. Specifically, it can be to use the discontinuity of the blood vessel bound...
Embodiment 2
[0071] see figure 2 , shows the parameter calculation method in the second embodiment of the present invention, which is used to calculate the hemodynamic parameters of blood vessels, the blood vessels include coronary arteries and aorta, and the method includes steps S11 to S19.
[0072] In step S11, the blood vessel image is processed to obtain pixel-based preliminary segmentation of the aorta and coronary artery respectively.
[0073] As an implementation, see image 3 , shows a specific implementation flowchart for processing the blood vessel image, including steps S111 to S113.
[0074] Step S111 , repeatedly performing blood vessel segmentation on the blood vessel image through a neural network.
[0075] Step S112, matching the segmented image output by the neural network each time with the corresponding pre-stored image, and feeding back the matching result to the neural network.
[0076] Wherein, the pre-stored image is a preset manually marked blood vessel templat...
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