A method for constructing a three-dimensional simulation model of fatty liver tissue
A technology of three-dimensional simulation and construction method, which is applied in 3D modeling, details related to 3D image data, image enhancement, etc. It can solve the problems of unclear morphological evolution of fat droplets, accurate quantitative interference of liver fat, and uniformity of influence.
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Embodiment 1
[0058] A method for constructing a three-dimensional simulation model of fatty liver tissue, such as figure 1 As shown, the steps involved are:
[0059] Step 1, staining the liver biopsy sample;
[0060] Step 2. Obtain a histogram of the two-dimensional size distribution of the real fat droplet and a two-dimensional nearest neighbor distance distribution histogram of the real fat droplet according to the statistics of the liver biopsy sample;
[0061] Step 3, calculating the histogram of the three-dimensional size distribution of fat droplets according to the histogram of the two-dimensional size distribution of the real fat droplets obtained in step two;
[0062] Step 4. Construct a plurality of grid points of the shape parameters and scale parameters of the three-dimensional nearest neighbor distance distribution of fat droplets, and combine the three-dimensional size distribution histogram of fat droplets obtained in step three to construct multiple three-dimensional simul...
Embodiment 2
[0099] A method for constructing a three-dimensional simulation model of fatty liver tissue, illustrated by three liver samples with different fat contents.
[0100] Step one includes:
[0101] Step 1.1. Collect 3 liver tissue samples according to clinical routine, the section thickness is 5um, stain with H&E, and the fat content of the biopsy samples is 2.46%, 7.24% and 20.80% respectively;
[0102] Step 1.2, perform image binarization processing on 3 liver tissue samples, such as figure 2 and 3 . Specifically, the fat droplet is approximated as a circle with a constant area and the same center of gravity in a two-dimensional plane, so as to count the two-dimensional size of the fat droplet and the two-dimensional nearest neighbor distance information.
[0103] Step 2: Statistically calculate the distribution histograms of the two-dimensional size of the fat droplet and the two-dimensional nearest neighbor distance in each biopsy sample image, and the group distance is 1u...
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