CN110782994A - Novel method for measuring epicardial fat by using mimics software - Google Patents
Novel method for measuring epicardial fat by using mimics software Download PDFInfo
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Abstract
The invention relates to the technical field of epicardial fat measurement, in particular to a novel method for measuring epicardial fat by adopting mimics software. Which comprises the following steps: importing the existing heart ct data into the mimics software; extracting and three-dimensionally reconstructing tissues, and automatically calculating by using MIMICS software to generate a coronal plane graph and a sagittal plane graph after introducing an original tomogram; performing interaction between MIMICS and RP rapid prototyping technologies through a triangular file format; setting threshold values, and extracting tissues with the gray values of the colored pixels falling between the threshold values; rapidly processing the scanned and input data, and outputting a corresponding file format for finite element analysis and computer simulation fluid dynamics; the fat content of each part such as epicardium is measured. In the novel method for measuring epicardium fat by using the mimics software, the content of fat of each part such as the epicardium can be accurately measured by using the mimics software, so that the distribution of heart fat is reflected, and the surface heart adipose tissue and the occurrence of atrial fibrillation can be observed conveniently through images.
Description
Technical Field
The invention relates to the technical field of epicardial fat measurement, in particular to a novel method for measuring epicardial fat by adopting mimics software.
Background
Cardiac fat includes intramyocardial fat and epicardial adipose tissue. Because the CT values of the adipose tissues and the myocardial tissues are different, the CT images can reflect the distribution of the heart fat, the heart adipose tissues and the atrial fibrillation are obviously related on the image observation surface, and the cardiomyopathy exists, so the heart CT is an important image means for researching the related relation between the heart fat and the arrhythmia. However, the CT image can reflect the distribution of the heart fat, and the fat content of each part such as the epicardium cannot be accurately measured.
Disclosure of Invention
The invention aims to provide a novel method for measuring epicardial fat by adopting mimics software, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides a novel method for measuring epicardial fat by using mimics software, which comprises the following steps:
s1, importing data, namely importing the existing heart ct data into the mimics software;
s2, extracting tissues and three-dimensionally reconstructing, and automatically calculating by MIMICS software to generate a coronal plane graph and a sagittal plane graph after introducing an original tomogram;
s3, rapid forming, namely, interacting between MIMICS and RP rapid forming technologies through a triangular file format;
s4, extracting corresponding tissues, setting threshold values and extracting tissues with the gray value of the coloring pixel falling between the threshold values;
s5, rapidly processing the scanned and input data by the reconstructed three-dimensional digital model, and outputting a corresponding file format for finite element analysis and computer simulation fluid dynamics;
and S6, measuring the fat content of each part such as epicardium.
Preferably, in S2, the tissue extraction and three-dimensional reconstruction steps include:
s2.1, contour modeling, wherein in the state of a segmentation function, the MIMICS automatically generates a contour on a separated mask, and the MEDCAD can automatically generate a local contour model under the condition of a given error;
s2.2, a support structure is established, interfaces in a SLICE format are established between the MIMICS and the plurality of RP machines, and the RP-SLICE module can automatically generate the support structure required by the RP model.
Preferably, in S2.2, the support structure is established by using an own RP-SLICE module in the MIMICS software.
Preferably, in S3, the rapid prototyping step is as follows:
s3.1, outputting a format, and setting a standard 3D file output format;
s3.2, setting parameters, selecting several parameters, reducing the number of triangular plates of an output file by an STL + module, and performing fairing processing on the 3D model by performing interpolation operation on the image.
Preferably, in S3.2, the interpolation operation is linear interpolation by DDA method, and taking a straight line in which the first quadrant passes through the origin of coordinates as an example, the start point is (0,0) and the end point is (x)
0,y
0) Then the equation of the straight line is:
the parametric equation with t as a parameter is as follows:
carrying out differential operation to obtain:
the integration operation can be carried out to obtain:
the accumulated equation is:
taking Δ t as 1, the above becomes:
preferably, in S5, the step of reconstructing the three-dimensional digital model is as follows:
s5.1, establishing a 3D model through point cloud data in MIMICS;
s5.2, in the FEA module, the mesh re-dividing function of MIMICS is used for re-dividing the 3D model mesh;
s5.3, outputting the data to FEA software such as Patran Neutral, Ansys, Abaqus surface and the like under an FEA module;
s5.4, converting the surface grids into body grids for pretreatment;
s5.5, carrying out MIMICS grid resculpting.
Preferably, in S5.4, the step of converting the surface mesh into the volume mesh for preprocessing comprises:
s5.4.1, inputting Patran, Ansys and Abaqus body grid files in the FEA module;
s5.4.2, distributing materials to the volume grids based on the scanning data in the FEA module;
s5.4.3, the FEA module outputs the volume grid after material distribution to FEA software such as Patran, Ansys, or Abaqus.
Compared with the prior art, the invention has the beneficial effects that: in the novel method for measuring epicardium fat by using the mimics software, the content of fat of each part such as the epicardium can be accurately measured by using the mimics software, so that the distribution of heart fat is reflected, and the surface heart adipose tissue and the occurrence of atrial fibrillation can be observed conveniently through images.
Drawings
FIG. 1 is an overall flow diagram of the present invention;
FIG. 2 is a block diagram of the tissue extraction and three-dimensional reconstruction steps of the present invention;
FIG. 3 is a block diagram of the rapid prototyping step of the present invention;
FIG. 4 is a block diagram of the steps of the reconstructed three-dimensional digital model of the present invention;
FIG. 5 is a block diagram of the conversion of a surface mesh into a volume mesh for preprocessing steps of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, the present invention provides a technical solution:
the invention provides a novel method for measuring epicardial fat by using mimics software, which comprises the following steps:
s1, importing data, namely importing the existing heart ct data into the mimics software;
s2, extracting tissues and three-dimensionally reconstructing, and automatically calculating by MIMICS software to generate a coronal plane graph and a sagittal plane graph after introducing an original tomogram;
s3, rapid forming, namely, interacting between MIMICS and RP rapid forming technologies through a triangular file format;
s4, extracting corresponding tissues, setting threshold values and extracting tissues with the gray value of the coloring pixel falling between the threshold values;
the threshold value for fat setting is generally chosen to be between-200 and-50 HU, according to the current major literature references, and some are chosen to be between-190 and-30 HU. The extraction of adipose tissue was performed using the 3D LIVEWIRE tool in MIMICS software.
S5, rapidly processing the scanned and input data by the reconstructed three-dimensional digital model, and outputting a corresponding file format for finite element analysis and computer simulation fluid dynamics;
and S6, measuring the fat content of each part such as epicardium.
In this embodiment, in S2, the tissue extraction and three-dimensional reconstruction steps are as follows:
s2.1, contour modeling, wherein in the state of a segmentation function, the MIMICS automatically generates a contour on a separated mask, and the MEDCAD can automatically generate a local contour model under the condition of a given error;
s2.2, a support structure is established, interfaces in a SLICE format are established between the MIMICS and the plurality of RP machines, and the RP-SLICE module can automatically generate the support structure required by the RP model.
Wherein all these entities can be exported in iges format to CAD software for implant fabrication.
Further, in S2.2, the support structure is established by using an own RP-SLICE module in MIMICS software.
In S3, the rapid prototyping step is as follows:
s3.1, outputting a format, and setting a standard 3D file output format;
s3.2, setting parameters, selecting several parameters, reducing the number of triangular plates of an output file by an STL + module, and performing fairing processing on the 3D model by performing interpolation operation on the image.
The RP-SLICE module can automatically generate a supporting structure required by the RP model, large files can be processed by using the RP SLICE technology, high resolution is maintained, and when a SLICE file is established, the resolution of the RP model is improved by using a cubic interpolation algorithm.
Wherein, the cubic interpolation algorithm is defined as: if the function f (x)
j)＝y
jJ is 0,1 …, n, and the cubic spline function s (x) for this node set satisfies the interpolation condition:
s(x
j)＝y
j,j＝0,1…,n
this cubic spline function s (x) is called the cubic spline interpolation function.
It is worth to be noted that the Rp-slice can perform the best and most accurate data conversion in a short time, and output SLI, SLC format to 3D System, CLI format to EOS, and the high-order interpolation algorithm can change the scanned data into a 3D solid model with a perfect surface, wherein the high-order interpolation algorithm selects lagrange interpolation algorithm or piecewise cubic Hermite interpolation algorithm.
The Lagrange interpolation algorithm is an n-th order polynomial interpolation, and the problem solving method is to construct an interpolation basis function and then solve the n-th order polynomial interpolation. To pairLagrange's n-th order interpolation polynomial, first, n +1 interpolation points x are selected
0,x
1,......x
nThe above-mentioned n-th-order interpolation basis function,
with the n +1 interpolation basis functions of n times, Lagrange interpolation polynomial of n times can be easily written out, and the specific expression is
The Lagrange interpolation principle numerical table is as follows:
interpolation numerical table
Further, the method of Lagrange interpolation is as follows: for a given number n of interpolation nodes x
0,x
1,......x
nAnd the corresponding function value y
0,y
1,y
2,......,y
nBy using Lagrange interpolation polynomial of degree n, the function value y corresponding to any x in the interpolation interval can be solved by using the following expression ln (x).
Still further, the mathematical expression of the Lagrange interpolation polynomial ln (x) of degree n in the interpolation value table is:
wherein l
i(x) (i ═ 0,1,2.., n) is the interpolation basis function, i.e., n
The remainder of the Lagrange interpolation polynomial is
And wherein ω (x) ═ x (x-x)
0)(x-x
1)...(x-x
n)。
The piecewise cubic Hermite interpolation algorithm is defined as follows: assuming that the known function f (x) is in the interpolation interval [ p, q ]]N +1 mutually different nodes x
i(i ═ 0, 1.. times.n) satisfies f (x)
i)＝f
iAnd f' (x)
i)＝f
i' (i ═ 0,1,2.., n), if the presence of function g (x) satisfies the following condition:
① G (x) a polynomial degree of 3 over each cell;
②G(x)∈C
1[a,b]；
③G(x
i)＝f(x
i)，G′(x
i)＝f′(x
i)，i＝(0,1,...,n)；
then G (x) is f (x) at n +1 nodes x
iA segmented cubic Hermite interpolation polynomial above;
therefore, the first and second electrodes are formed on the substrate,
in S3.2, the interpolation operation is linear interpolation by DDA method, and for example, a straight line in which the first quadrant passes through the origin of coordinates is taken as an example, where the starting point is (0,0) and the end point is (x)
0,y
0) Then the equation of the straight line is:
the parametric equation with t as a parameter is as follows:
carrying out differential operation to obtain:
the integration operation can be carried out to obtain:
the accumulated equation is:
taking Δ t as 1, the above becomes:
in this embodiment, in S5, the steps of the reconstructed three-dimensional digital model are as follows:
s5.1, establishing a 3D model through point cloud data in MIMICS;
s5.2, in the FEA module, the mesh re-dividing function of MIMICS is used for re-dividing the 3D model mesh;
s5.3, outputting the data to FEA software such as Patran Neutral, Ansys, Abaqus surface and the like under an FEA module;
s5.4, converting the surface grids into body grids for pretreatment;
s5.5, carrying out MIMICS grid resculpting.
The mesh re-dividing function of MIMICS can obviously improve the quality and processing speed of the STL model, and can conveniently convert irregular triangular plates into triangular plates approaching to equal sides.
Specifically, in S5.4, the step of converting the surface mesh into the volume mesh for preprocessing includes:
s5.4.1, inputting Patran, Ansys and Abaqus body grid files in the FEA module;
s5.4.2, distributing materials to the volume grids based on the scanning data in the FEA module;
s5.4.3, the FEA module outputs the volume grid after material distribution to FEA software such as Patran, Ansys, or Abaqus.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. A novel method for measuring epicardial fat by adopting mimics software comprises the following steps:
s1, importing data, namely importing the existing heart ct data into the mimics software;
s2, extracting tissues and three-dimensionally reconstructing, and automatically calculating by MIMICS software to generate a coronal plane graph and a sagittal plane graph after introducing an original tomogram;
s3, rapid forming, namely, interacting between MIMICS and RP rapid forming technologies through a triangular file format;
s4, extracting corresponding tissues, setting threshold values and extracting tissues with the gray value of the coloring pixel falling between the threshold values;
s5, rapidly processing the scanned and input data by the reconstructed three-dimensional digital model, and outputting a corresponding file format for finite element analysis and computer simulation fluid dynamics;
and S6, measuring the fat content of each part such as epicardium.
2. The novel method for measuring epicardial fat using mimics software as set forth in claim 1, wherein: in S2, the tissue extraction and three-dimensional reconstruction steps are as follows:
s2.1, contour modeling, wherein in the state of a segmentation function, the MIMICS automatically generates a contour on a separated mask, and the MEDCAD can automatically generate a local contour model under the condition of a given error;
s2.2, a support structure is established, interfaces in a SLICE format are established between the MIMICS and the plurality of RP machines, and the RP-SLICE module can automatically generate the support structure required by the RP model.
3. The novel method for measuring epicardial fat using mimics software as set forth in claim 2, wherein: in S2.2, the support structure is established by adopting an RP-SLICE module in MIMICS software.
4. The novel method for measuring epicardial fat using mimics software as set forth in claim 1, wherein: in S3, the rapid prototyping step is as follows:
s3.1, outputting a format, and setting a standard 3D file output format;
s3.2, setting parameters, selecting several parameters, reducing the number of triangular plates of an output file by an STL + module, and performing fairing processing on the 3D model by performing interpolation operation on the image.
5. The novel method for measuring epicardial fat using mimics software according to claim 4, characterized in that: in S3.2, the interpolation operation is linear interpolation by DDA method, taking a straight line where the first quadrant passes through the origin of coordinates as an example, the starting point is (0,0) and the end point is (x)
0,y
0) Then the equation of the straight line is:
the parametric equation with t as a parameter is as follows:
carrying out differential operation to obtain:
the integration operation can be carried out to obtain:
the accumulated equation is:
taking Δ t as 1, the above becomes:
6. the novel method for measuring epicardial fat using mimics software as set forth in claim 1, wherein: in S5, the steps of reconstructing the three-dimensional digital model are as follows:
s5.1, establishing a 3D model through point cloud data in MIMICS;
s5.2, in the FEA module, the mesh re-dividing function of MIMICS is used for re-dividing the 3D model mesh;
s5.3, outputting the data to FEA software such as Patran Neutral, Ansys, Abaqus surface and the like under an FEA module;
s5.4, converting the surface grids into body grids for pretreatment;
s5.5, carrying out MIMICS grid resculpting.
7. The novel method for measuring epicardial fat using mimics software of claim 6, wherein: in S5.4, the step of converting the surface mesh into a body mesh for preprocessing includes:
s5.4.1, inputting Patran, Ansys and Abaqus body grid files in the FEA module;
s5.4.2, distributing materials to the volume grids based on the scanning data in the FEA module;
s5.4.3, the FEA module outputs the volume grid after material distribution to FEA software such as Patran, Ansys, or Abaqus.
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