An automatic measurement method for mitral valve leaflet length based on 3D to 2D morphological transformation

Abstract

The present invention proposes a method for automatically measuring the length of the mitral valve leaflets based on 3D to 2D morphological transformation. The method first obtains three-dimensional medical image data of the patient's heart and extracts six partitions of the mitral valve and related heart structures. By fitting the mitral valve structure point set, the orthogonal plane is calculated, and the cKDTree algorithm is used to determine the connecting areas of each partition, and the corresponding projection plane is established. The contour of the projected point set is then extracted by the Alpha shapes algorithm and corrected to a linear three-dimensional point set, and finally the length of each partitioned leaflet is calculated. This method improves the accuracy, consistency and efficiency of measurement through automation technology, reduces human errors, is applicable to a variety of three-dimensional medical imaging data, and provides a more reliable basis for the clinical diagnosis and treatment of mitral valve disease.

Description

Technical Field

[0001] The present invention belongs to the field of medical image processing technology, and specifically relates to a method for measuring the six-section leaflet of the mitral valve based on three-dimensional medical image data. The present invention utilizes a 3D-to-2D morphological transformation technique to automatically measure the length of the six-section leaflet of the mitral valve. Background Art

[0002] The mitral valve is a vital valve structure between the left ventricle and left atrium of the heart. Its normal function is crucial for maintaining the cardiovascular system. The mitral valve consists of anterior and posterior leaflets, which are further subdivided into six zones according to the Carpentier classification: A1, A2, A3, and P1, P2, and P3. Accurately measuring the leaflet lengths of these six zones is crucial for diagnosing mitral valve disease, assessing its severity, and formulating treatment plans.

[0003] Traditional measurement of mitral valve leaflet length mainly relies on two-dimensional echocardiography, which has the following limitations:

[0004] 1. Two-dimensional imaging cannot fully display the three-dimensional structure of the mitral valve, which may lead to measurement errors in clinical diagnosis;

[0005] 2. The repeatability and comparability of measurement results are poor and rely on the operator’s experience;

[0006] 3. It is difficult to accurately distinguish the six partitions, especially the boundaries between adjacent partitions.

[0007] With the development of medical imaging technology, three-dimensional CT and MRI have provided new possibilities for observing the structure of the mitral valve. However, how to accurately extract the leaflet lengths of the six mitral valve segments from these three-dimensional data remains a challenge. Currently, most methods still rely on manual measurement, which is not only time-consuming and labor-intensive, but also easily affected by subjective factors, making it difficult to ensure the consistency and accuracy of the measurement. Therefore, it is of great clinical significance to develop a method that can automatically, accurately, and repeatably measure the leaflet lengths of the six mitral valve segments. This method should be able to fully utilize three-dimensional medical image data, overcome the limitations of two-dimensional measurement, reduce human errors, improve measurement efficiency and accuracy, provide doctors with more accurate diagnostic basis, and reduce the risk of misdiagnosis and delayed treatment.

[0008] This invention aims to address the above-mentioned issues by proposing an automated mitral valve leaflet length measurement method based on 3D-to-2D morphological transformation. This method automatically identifies the mitral valve structure by processing 3D medical image data. Using a series of mathematical algorithms, the 3D leaflet structure is converted into a 2D projection representation, ultimately enabling precise measurement of the leaflet lengths in six sections. This method not only improves measurement accuracy and consistency but also significantly enhances work efficiency, providing a more reliable basis for the diagnosis and treatment of mitral valve-related diseases. Summary of the Invention

[0009] The present invention aims to address the current lack of analysis and processing of three-dimensional data of the left mitral valve structure and propose an automatic measurement method for mitral valve leaflet length based on 3D to 2D morphological transformation, which includes the following steps:

[0010] Step 1: Acquire three-dimensional medical image data of the patient's heart;

[0011] Step 2: Extract the mitral valve structure from the acquired 3D medical image data, including the six partitions of the mitral valve leaflet structure: A1 partition, A2 partition, A3 partition, P1 partition, P2 partition, and P3 partition. At the same time, extract related cardiac structures, including the aorta, left ventricle, left myocardium, and left atrium.

[0012] Step 3: Based on the extracted mitral valve structure, the orthogonal plane of the mitral valve annulus structure is calculated by fitting the structural point set;

[0013] Step 4: Based on the orthogonal planes calculated in step 3, use the mitral valve A1, P1 partition structure point set, and the A3, P3 partition structure point set to calculate the intersection points of the mitral valve anterior leaflet and posterior leaflet contours in sequence;

[0014] Step 5: Based on the orthogonal plane of the mitral valve annulus and any two points in space, a unique plane expression orthogonal to the plane is constructed to facilitate further length measurement.

[0015] Step 6: Use the cKDTree algorithm to determine the connecting areas between the six partitions of the leaflet, and define the end close to the left atrium as the vertex and the end close to the left ventricle as the base.

[0016] Step 7: Using the apex and base points of the connecting areas of the six mitral valve partitions determined in step 6, and taking the projection direction provided by the unique plane constructed in step 5 as a reference, determine the leaflet projection planes of the six partitions in turn;

[0017] Step 8: Filter the point set of the mitral valve based on the spatial diagonal distance and calculate the corresponding projection point set;

[0018] Step 9: Using the Alpha shapes algorithm, extract the contours of the projection points of each partition for the projection point sets of the six partitions, and further correct them into linear three-dimensional point sets;

[0019] Step 10: Calculate the spatial length of the three-dimensional point set corresponding to each partition, and ultimately determine the leaflet lengths of the six partitions of the mitral valve.

[0020] Furthermore, in step 1, the three-dimensional medical image data may be any medical image data containing information of the left heart region of the human body.

[0021] Furthermore, in step 2, medical annotation software is used to manually annotate the structure, or an AI deep learning algorithm is used to automatically segment the main structures of the mitral valve; the deep learning algorithms include nnUNet and SwinUNETR; the six partitions of the mitral valve after annotation or segmentation are A1 partition, A2 partition, A3 partition, P1 partition, P2 partition and P3 partition respectively.

[0022] Furthermore, in step 3, the orthogonal plane of the mitral valve ring structure is determined by fitting the structure point set. m The specific method is:

[0023]

[0024] H=X T X

[0025]

[0026]

[0027] where p i is the i-th point in the mitral valve structure point set, n is the total number of points in the point set, x i is the point after centering, X is the matrix of all the centering points, X T is its transpose, λ is the eigenvalue, is the corresponding eigenvector, is the unit normal vector of the fitted plane, and the parameter vector of the final plane is Orthogonal Plane m The equation is expressed as:

[0028]

[0029] Furthermore, in step 4, based on the calculated orthogonal plane, the intersection point set of the A1 and P1 partition structures and the intersection point set of the A3 and P3 partition structures are calculated to calculate the left and right intersection points of the outer contour. The specific steps are as follows:

[0030] Step 4.1: Using the A3 and P3 partition structures, calculate the set of all adjacent points at the intersection of the two structures, which is called PointsLCC. Similarly, using the A1 and P1 partition structures, calculate the set of all adjacent points at the intersection of the two structures, which is called PointsRCC.

[0031] Step 4.2: Reconstrain the mitral valve annulus orthogonal plane calculated in step 3 m The direction of the left atrium is defined as the positive direction;

[0032] Step 4.3: Calculate the distance between each point in the two sets of points, PointsLCC and PointsRCC, and Plane m Distance Dis PointsLcc 、Dis PointsRcc ;

[0033] Step 4.4: Select the points with the largest distance from the two sets of points and count them as PointLC and PointRC respectively.

[0034] PointLC=PointsLCC[Index[max(Dis PointsLcc )]]

[0035] PointRC=PointsRCC[Index[max(Dis PointsRcc )]]

[0036] Among them, Index[max(Dis)] is the index of the maximum distance point, PointLC is the intersection vertex of the mitral valve A3 and P3 partition structures, and PointRC is the intersection vertex of the mitral valve A1 and P1 partition structures.

[0037] Furthermore, in step 5, based on the orthogonal plane Plane m and two arbitrary points p0 and p1 in space, get the line segment p0-p1 and the plane m The only orthogonal plane l expression.

[0038] Furthermore, in step 6, the cKDTree algorithm is used to calculate the vertex near the left atrium. and the bottom point near one end of the left ventricle The specific steps are as follows:

[0039] Step 6.1: Use the kd tree to extract the point sets of the connected areas of the mitral valve A1-A2 partition, A2-A3 partition, P1-P2 partition and P2-P3 partition, and count them as Points A1-A2 、Points A2-A3 、PointsP1-P2 、Points P2-P3 ;

[0040] Step 6.2: Use the left atrium and left ventricle structures obtained in step 2 to calculate the center points of the left atrium and left ventricle three-dimensional structures respectively, which are recorded as Center_Point Atrium 、Center_Point Ventricle ;

[0041] Step 6.3: Calculate the center point of the left atrium separately Atrium With Points A1-A2 、Points A2-A3 、Points P1-P2 、Points P2-P3 The distance of the point set is calculated by selecting the point with the smallest distance as the vertex, which is: The following vertex point set is formed:

[0042]

[0043] Step 6.4: Calculate the center point of the left ventricle Center_Point Ventricle With Points A1-A2 、Points A2-A3 、Points P1-P2 、Points P2-P3 The distance of the point set is calculated by selecting the point with the smallest distance as the bottom point, which is calculated as follows: The following bottom point set is formed:

[0044]

[0045] Furthermore, in step 7, based on the apex and base points determined in step 6, the leaflet projection plane of each partition is calculated respectively, as follows:

[0046] Step 7.1: Use Weighted calculation gets p0 p1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane A2_Proj_Plane;

[0047] Step 7.2: Use Weighted calculation gets p0 p1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane P2_Proj-Plane;

[0048] Step 7.3: Using PointLC, Weighted calculation gets p0 P1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane A1_Proj_Plane;

[0049] Step 7.4: PointLC, Weighted calculation gets p0 P1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane P1_Proj_Plane;

[0050] Step 7.5: Using PointRC, Weighted calculation gets p0 P1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane A3_Proj_Plane.

[0051] Step 7.6: PointRC, Weighted calculation gets p0 P1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane P3_Proj_Plane.

[0052] Furthermore, in step 8, the specific steps of using the mitral valve point set to obtain the projection point set are as follows:

[0053] Step 8.1: Calculate the distance D from each point in each partition of the mitral valve to the corresponding projection plane. i :

[0054]

[0055] Among them, ax i +by i +CZ i +d∈(A1 / A2 / A3 / P1 / P2 / P3_Proj_Plane), {(x i ,y i , z i )}∈(A1 / A2 / A3 / P1 / P2 / P3 Points) is the point set of each partition;

[0056] Step 8.2: Based on the calculated distance, select points whose distance from the projection plane is less than the threshold threshold to form a new point set P′. The threshold is defined as: (1, 1, 1);

[0057] Step 8.3: For each point p in the filtered point set P′ i , project it onto the plane and get the projection point p i，proj :

[0058]

[0059] in, is the normal vector of the projection reference plane constructed in step 5, p i The i-th three-dimensional coordinate point in any screening point set P′ in the six partitions is obtained. So far, six groups of projection point sets are obtained in sequence for the six partitions of the mitral valve.

[0060] Furthermore, in step 9, the Alpha shapes algorithm and spline difference are used to extract the final leaflet point set. The specific steps are as follows:

[0061] Step 9.1: For the point set and parameter α, the alpha shape is described as

[0062]

[0063] Among them S α Convex hull contours that make up the shape;

[0064] Step 9.2: Projection point set of each partition in turn Apply the Alpha shapes algorithm in step 9.1 to generate the corresponding contour curve

[0065] Step 9.3: Use the center point of the left atrium and left ventricle Center_Point Atrium 、Center_Point Ventricle , determine the starting and ending points of each group of points and then shape the Alpha curve of each partition Corrected to a linear point set

[0066] Step 9.4: Apply cubic spline interpolation to the corrected linear point set, for Generate a uniform three-dimensional resampling point set, denoted as

[0067] Furthermore, in step 10, the distance between each point is calculated in sequence using the uniformly sampled point set:

[0068]

[0069] Among them, p i and p i+1 are two adjacent points in the same partition;

[0070] Calculate the leaflet length of each partition in turn. For each partition, accumulate the distances between all points and calculate the corresponding leaflet length, specifically:

[0071]

[0072] Among them, L A1 , L A2 , L A3 Represents the leaflet length of the three divisions of the anterior leaflet of the mitral valve, L P1 , L P2 , L P3 Represents the leaflet lengths of the three divisions of the posterior mitral leaflet.

[0073] Technical Effects

[0074] The automatic measurement method of mitral valve leaflet length based on 3D to 2D morphological transformation proposed in the present invention has significant technical advantages. First, the method has a high degree of automation and can automatically process three-dimensional medical image data without manual intervention, which greatly improves the measurement efficiency. Through 3D to 2D conversion and precise mathematical algorithms, this method can accurately measure the leaflet lengths of the six partitions of the mitral valve, reducing the measurement errors caused by human operation. In addition, due to the use of an automated algorithm, this method has a high degree of consistency among different operators or multiple measurements, ensuring the repeatability and stability of the measurement results.

[0075] This comprehensive method can simultaneously assess all six mitral valve zones, providing comprehensive valve data for clinical diagnosis. Compared with traditional manual measurement, this method significantly reduces the influence of subjective factors on measurement results, significantly improving objectivity and reliability. Furthermore, this method is applicable to a variety of 3D medical imaging data, such as CT and MRI, enhancing its adaptability and flexibility in clinical practice.

[0076] Finally, the automated measurement process not only shortens data processing time but also enables doctors to obtain the required measurement results more quickly. These technical effects make this invention a significant advancement in the field of mitral valve leaflet length measurement, providing a more reliable and efficient tool for the diagnosis and treatment of related diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 This is a flow chart of the automatic mitral valve leaflet length measurement solution based on 3D to 2D morphological transformation;

[0078] Figure 2 This is the six-partition diagram described in step 2;

[0079] Figure 3 is the orthogonal plane diagram described in step 3;

[0080] Figure 4 PointLC, PointRL, Schematic diagram of eight key points;

[0081] Figure 5 7 is a schematic diagram of the projection surface of each of the six partitions of the mitral valve described in step 7;

[0082] Figure 6 is a schematic diagram of a point set of leaflet lengths in each of the six partitions of the mitral valve described in step 9;

[0083] Figure 7 This is a schematic diagram of the leaflet length results for each of the six partitions of the mitral valve described in step 10. DETAILED DESCRIPTION

[0084] The present invention will be further described below in conjunction with specific examples. It should be understood that the examples are only intended to illustrate the present invention and are not intended to limit the scope of protection of the present invention. In addition, it should be understood that after reading the disclosure of the present invention, those skilled in the art may make various changes or modifications to the present invention, and these equivalent forms also fall within the scope of protection defined by the present invention.

[0085] The present invention proposes a method for automatically measuring the length of mitral valve leaflets based on 3D to 2D morphological transformation. Figure 1 As shown, the following steps are included:

[0086] Step 1: Acquire three-dimensional medical image data of the patient's heart. The three-dimensional medical image data can come from a variety of imaging technologies, including computed tomography (CT), computed tomography angiography (CTA), magnetic resonance imaging (MRI), or ultrasound (US). To ensure the accuracy of subsequent analysis, the imaging results must cover all relevant structures of the patient's heart. Furthermore, the image data must undergo preprocessing, including denoising and standardization, to ensure data quality. These processing steps can be implemented using medical image processing software.

[0087] Step 2: Extract the mitral valve structure from the acquired 3D medical image data, including the six partitions of the mitral valve leaflet structure, namely, A1 partition, A2 partition, A3 partition, P1 partition, P2 partition, and P3 partition. At the same time, extract related cardiac structures, including the aorta, left ventricle, left myocardium, and left atrium, such as Figure 2As shown in the figure, in this step, the image data can be segmented by manual annotation or using an AI deep learning algorithm. For manual annotation, doctors can use professional annotation assistance software such as 3DSlicer or MIMICS. For automatic segmentation, deep learning-based segmentation algorithms such as nnUNet or SwinUNETR are used. These algorithms require training on a large amount of annotated medical image data to accurately identify the six subregions of the mitral valve and other related cardiac structures. Automatic segmentation can greatly improve the efficiency and accuracy of segmentation.

[0088] Step 3: Based on the extracted mitral valve structure, calculate the orthogonal plane of the mitral valve ring structure by fitting the structure point set m ,like Figure 3 As shown, the specific method is:

[0089] First, calculate the centering of the point set:

[0090]

[0091] Next, construct the matrix X and calculate its eigenvalues ​​and eigenvectors:

[0092]

[0093] Through these steps, we finally get the expression of the orthogonal plane parameters:

[0094]

[0095] where p i is the i-th point in the mitral valve structure point set, n is the total number of points in the point set, x i is the point after centering, X is the matrix of all the centering points, X T is its transpose, λ is the eigenvalue, is the corresponding eigenvector, is the unit normal vector of the fitted plane, and the parameter vector of the final plane is Orthogonal Plane m The equation is expressed as:

[0096]

[0097] Step 4: Based on the orthogonal planes calculated in step 3, use the mitral valve A1, P1 partition structure point set, and the A3, P3 partition structure point set to calculate the intersection points of the mitral valve anterior leaflet and posterior leaflet contours in sequence. The specific steps are as follows:

[0098] Step 4.1: Using the A3 and P3 partition structures, calculate the set of all adjacent points at the intersection of the two structures, which is called PointsLCC. Similarly, using the A1 and P1 partition structures, calculate the set of all adjacent points at the intersection of the two structures, which is called PointsRCC.

[0099] Step 4.2: Reconstrain the mitral valve annulus orthogonal plane calculated in step 3 m direction, and the direction pointing to the left atrium is defined as the positive direction

[0100]

[0101] Step 4.3: Calculate the distance between each point in the two sets of points, PointsLCC and PointsRCC, and Plane m Distance Dis PointsLcc 、Dis PointsRcc

[0102]

[0103] Step 4.4: Select the points with the largest distance from the two sets of points and count them as PointLC and PointRC respectively.

[0104] PointLC=PointsLCC[Index[max(Dis PointsLcc )]]

[0105] PointRC=PointsRCC[Index[max(Dis PointsRcc )]]

[0106] Among them, Index[max(Dis)] is the index of the maximum distance point, PointLC is the intersection vertex of the mitral valve A3 and P3 partition structures, and PointRC is the intersection vertex of the mitral valve A1 and P1 partition structures, such as Figure 4 shown.

[0107] Step 5: Orthogonal Plane Based on the Mitral Annuli m and two arbitrary points p0 and p1 in space, get the line segment P0-p1 and the plane m The only orthogonal plane l expression.

[0108]

[0109]

[0110]

[0111]

[0112] Where p0 and p1 are any two points in space, It's Plane m The normal vector of Is orthogonal to Plane m The vector of the line segment p0-p1, d new Is a constant term, then the plane cluster Plane l The expression is:

[0113]

[0114] Step 6: Use the cKDTree algorithm to determine the connecting areas between the six partitions of the leaflet and define the vertices close to the left atrium. and the bottom point near one end of the left ventricle The specific steps are as follows:

[0115] Step 6.1: Use the kd tree to extract the point sets of the connected areas of the mitral valve A1-A2 partition, A2-A3 partition, P1-P2 partition and P2-P3 partition, and count them as Points A1-A2 、Points A2-A3 、Points P1-P2 、Points P2-P3 ;

[0116] Step 6.2: Use the left atrium and left ventricle structures obtained in step 2 to calculate the center points of the left atrium and left ventricle three-dimensional structures respectively, which are recorded as Center_Point Atrium 、Center_Point Ventricle ;

[0117] Step 6.3: Calculate the center point of the left atrium separately Atrium With Points A1-A2 、Points A2-A3 、Points P1-P2 、Points P2-P3 The distance of the point set is calculated by selecting the point with the smallest distance as the vertex, which is: The following vertex point set is formed:

[0118]

[0119] Step 6.4: Calculate the center point of the left ventricle Center_Point Ventricle With Points A1-A2 、Points A2-A3 、Points P1-P2 、PointsP2-P3 The distance of the point set is calculated by selecting the point with the smallest distance as the bottom point, which is calculated as follows: The following bottom point set is formed:

[0120]

[0121] Step 7: Based on the vertex and base points determined in step 6, calculate the leaflet projection plane of each partition, such as Figure 5 As shown, the steps are as follows:

[0122] Step 7.1: Use The weighted calculation gets p0p1, which is then introduced into the plane obtained in step 5. l Expression, and then obtain the projection plane A2_Proj_Plane

[0123]

[0124] Step 7.2: Use The weighted calculation gets p0p1, which is then introduced into the plane obtained in step 5. l Expression, and then obtain the projection plane P2_Proj_Plane

[0125]

[0126] Step 7.3: Using PointLC, The weighted calculation gets p0p1, which is then introduced into the plane obtained in step 5. l Expression, and then obtain the projection plane A1_Proj_Plane

[0127]

[0128] Step 7.4: PointLC, The weighted calculation gets p0p1, which is then introduced into the plane obtained in step 5. l Expression, and then obtain the projection plane P1_Proj_Plane

[0129]

[0130] Step 7.5: Using PointRC, The weighted calculation gets p0p1, which is then introduced into the plane obtained in step 5. l Expression, and then obtain the projection plane A3_Proj_Plane

[0131]

[0132] Step 7.6: PointRC, The weighted calculation gets p0p1, which is then introduced into the plane obtained in step 5. l Expression, and then obtain the projection plane P3_Proj_Plane

[0133]

[0134] Step 8: Filter the point set of the mitral valve based on the spatial diagonal distance and calculate the corresponding projection point set. The specific steps are as follows:

[0135] Step 8.1: Calculate the distance D from each point in each partition of the mitral valve to the corresponding projection plane. i :

[0136]

[0137] Among them, ax i +by i +cz i +d∈(A1 / A2 / A3 / P1 / P2 / P3_Proj_Plane),{(x i ,y i , z i )}∈(A1 / A2 / A3 / P1 / P2 / P3 Points) is the point set of each partition;

[0138] Step 8.2: Based on the calculated distance, select points whose distance from the projection plane is less than the threshold threshold to form a new point set P′. The threshold is defined as:

[0139] Step 8.3: For each point p in the filtered point set P′ i , project it onto the plane and get the projection point p i，proj :

[0140]

[0141] in, is the normal vector of the projection reference plane constructed in step 5, p i The i-th three-dimensional coordinate point in any screening point set P′ in the six partitions is obtained. So far, six groups of projection point sets are obtained in sequence for the six partitions of the mitral valve.

[0142] Step 9: Using the Alpha shapes algorithm, extract the contours of the projection points of each partition for the six partitions, and further correct them into a linear three-dimensional point set. The 2D point set of the leaflet length is equivalently calculated for the six partitions of the mitral valve as follows: Figure 6 The specific steps are as follows:

[0143] Step 9.1: For the point set and parameter α, the alpha shape is described as

[0144]

[0145] Among them S α Convex hull contours that make up the shape;

[0146] Step 9.2: Projection point set of each partition in turn Apply the Alpha shapes algorithm in step 9.1 to generate the corresponding contour curve

[0147] Step 9.3: Use the center point of the left atrium and left ventricle Center_Point Atrium 、Center_Point Ventricle , determine the starting and ending points of each group of points and then shape the Alpha curve of each partition Corrected to a linear point set

[0148] Step 9.4: Apply cubic spline interpolation to the corrected linear point set, for Generate a uniform three-dimensional resampling point set, denoted as

[0149] In this step, the Alpha Shapes algorithm generates a projected point outline for each partition. These points are further corrected using spline interpolation techniques to convert them into a linear 3D point set. This helps improve the accuracy of the calculation, especially in areas with significant curvature.

[0150] Step 10: Calculate the spatial length of the three-dimensional point set corresponding to each partition, and finally determine the leaflet lengths of the six partitions of the mitral valve. The calculation results of the leaflet lengths of the six partitions of the mitral valve are as follows: Figure 7 As shown, the specific method is:

[0151] Using the uniformly sampled point set, calculate the distance between each point in turn:

[0152]

[0153] Among them, p i and p i+1 are two adjacent points in the same partition;

[0154] Calculate the leaflet length of each partition in turn. For each partition, accumulate the distances between all points and calculate the corresponding leaflet length, specifically:

[0155]

[0156] Among them, L A1 , L A2 , L A3 , L P1 , L P2 , L P3 The three lengths of the six leaflets of the mitral valve are represented respectively. This method can effectively eliminate human errors, ensure the accuracy and consistency of the calculation results, and is suitable for the analysis of various medical imaging data.

Claims

1. A method for automatically measuring mitral valve leaflet length based on 3D to 2D morphological transformation, characterized in that: The following steps are involved: Step 1: Acquire three-dimensional medical image data of the patient's heart; Step 2: Extract the mitral valve structure from the acquired 3D medical image data, including the six partitions of the mitral valve leaflet structure: A1 partition, A2 partition, A3 partition, P1 partition, P2 partition, and P3 partition. At the same time, extract related cardiac structures, including the aorta, left ventricle, left myocardium, and left atrium. Step 3: Based on the extracted mitral valve structure, the orthogonal plane of the mitral valve annulus structure is calculated by fitting the structural point set; Step 4: Based on the orthogonal planes calculated in step 3, use the mitral valve A1, P1 partition structure point set, and the A3, P3 partition structure point set to calculate the intersection points of the mitral valve anterior leaflet and posterior leaflet contours in sequence; Step 5: Based on the orthogonal plane of the mitral valve annulus and any two points in space, a unique plane expression orthogonal to the plane is constructed to facilitate further length measurement. Step 6: Use the cKDTree algorithm to determine the connecting areas between the six partitions of the leaflet, and define the end close to the left atrium as the vertex and the end close to the left ventricle as the base. Step 7: Using the apex and base points of the connecting areas of the six mitral valve partitions determined in step 6, and taking the projection direction provided by the unique plane constructed in step 5 as a reference, determine the leaflet projection planes of the six partitions in turn; Step 8: Filter the point set of the mitral valve based on the spatial diagonal distance and calculate the corresponding projection point set; Step 9: Using the Alpha shapes algorithm, extract the contours of the projection points of each partition for the projection point sets of the six partitions, and further correct them into linear three-dimensional point sets; Step 10: Calculate the spatial length of the three-dimensional point set corresponding to each partition, and ultimately determine the leaflet lengths of the six partitions of the mitral valve.

2. The method for automatically measuring mitral valve leaflet length according to claim 1, characterized in that: In step 2, medical annotation software is used to manually annotate the structure, or an AI deep learning algorithm is used to automatically segment the main structures of the mitral valve; the deep learning algorithms include nnUNet and SwinUNETR; the six partitions of the mitral valve after annotation or segmentation are A1 partition, A2 partition, A3 partition, P1 partition, P2 partition and P3 partition.

3. The method for automatically measuring mitral valve leaflet length according to claim 2, characterized in that: In step 3, the orthogonal plane of the mitral valve ring structure is determined by fitting the structure point set. m The specific method is: H=X T X where p i is the i-th point in the mitral valve structure point set, n is the total number of points in the point set, x i is the point after centering, X is the matrix of all the centering points, X T is its transpose, λ is the eigenvalue, is the corresponding eigenvector, is the unit normal vector of the fitted plane, and the parameter vector of the final plane is Orthogonal Plane m The equation is expressed as:

4. The method for automatically measuring mitral valve leaflet length according to claim 3, characterized in that: In step 4, based on the calculated orthogonal plane, the intersection points of the left and right outer contours are calculated by calculating the intersection point set of the A1 and P1 partition structures and the intersection point set of the A3 and P3 partition structures. The specific steps are as follows: Step 4.1: Using the A3 and P3 partition structures, calculate the set of all adjacent points at the intersection of the two structures, which is called PointsLCC. Similarly, using the A1 and P1 partition structures, calculate the set of all adjacent points at the intersection of the two structures, which is called PointsRCC. Step 4.2: Reconstrain the mitral valve annulus orthogonal plane calculated in step 3 m The direction of the left atrium is defined as the positive direction; Step 4.3: Calculate the distance between each point in the two sets of points, PointsLCC and PointsRCC, and Plane m Distance Dis PointsLcc 、Dis PointsRcc ; Step 4.4: Select the points with the largest distance from the two sets of points and count them as PointLC and PointRC respectively. PointLC=PointsLCC[Index[max(Dis PointsLcc )]] PointRC=PointsRCC[Index[max(Dis PointsRcc )]] Among them, Index[max(Dis)] is the index of the maximum distance point, PointLC is the intersection vertex of the mitral valve A3 and P3 partition structures, and PointRC is the intersection vertex of the mitral valve A1 and P1 partition structures.

5. The method for automatically measuring the length of the mitral valve leaflets according to claim 4, characterized in that: In step 5, based on the orthogonal plane Plane m and two arbitrary points p0 and p1 in space, get the line segment p0-p1 and the plane m The only orthogonal plane l expression.

6. The method for automatically measuring mitral valve leaflet length according to claim 5, characterized in that: Furthermore, in step 6, the cKDTree algorithm is used to calculate the vertex near the left atrium. and the bottom point near one end of the left ventricle The specific steps are as follows: Step 6.1: Use the kd tree to extract the point sets of the connected areas of the mitral valve A1-A2 partition, A2-A3 partition, P1-P2 partition and P2-P3 partition, and count them as Points A1-A2 、Points A2-A3 、Points P1-P2 、Points P2-P3 ; Step 6.2: Using the left atrium and left ventricle structures obtained in step 2, calculate the center points of the left atrium and left ventricle three-dimensional structures respectively, and calculate them as Step 6.3: Calculate the center point of the left atrium separately With Points A1-A2 、Points A2-A3 、Points P1-P2 、Points P2-P3 The distance of the point set is calculated by selecting the point with the smallest distance as the vertex, which is: The following vertex point set is formed: Step 6.4: Calculate the center point of the left ventricle separately With Points A1-A2 、Points A2-A3 、Points P1-P2 、Points P2-P3 The distance of the point set is calculated by selecting the point with the smallest distance as the bottom point, which is calculated as follows: The following bottom point set is formed:

7. The method for automatically measuring mitral valve leaflet length according to claim 6, characterized in that: In step 7, based on the apex and base points determined in step 6, the leaflet projection plane of each partition is calculated respectively, as follows: Step 7.1: Use Weighted calculation gets p0 p1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane Step 7.2: Use Weighted calculation gets p0 p1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane Step 7.3: Using PointLC, Weighted calculation gets p0 p1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane Step 7.4: PointLC, Weighted calculation gets p0 p1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane Step 7.5: Using PointRC, Weighted calculation gets p0 p1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane Step 7.6: PointRC, Weighted calculation gets p0 p1, and put it into the plane Plane obtained in step 5 l Expression, and then obtain the projection plane 8. The method for automatically measuring mitral valve leaflet length according to claim 7, characterized in that: In step 8, the specific steps of using the mitral valve point set to obtain the projection point set are as follows: Step 8.1: Calculate the distance D from each point in each partition of the mitral valve to the corresponding projection plane. i : in, is the point set for each partition; Step 8.2: Based on the calculated distance, select points whose distance from the projection plane is less than the threshold threshold to form a new point set P′. The threshold is defined as: Step 8.3: For each point p in the filtered point set P′ i , project it onto the plane and get the projection point p i，proj : in, is the normal vector of the projection reference plane constructed in step 5, p i The i-th three-dimensional coordinate point in any screening point set P′ in the six partitions is obtained. So far, six groups of projection point sets are obtained in sequence for the six partitions of the mitral valve.

9. The method for automatically measuring mitral valve leaflet length according to claim 8, characterized in that: In step 9, the Alpha shapes algorithm and spline interpolation are used to extract the final leaflet point set. The specific steps are as follows: Step 9.1: For the point set and parameter α, the alpha shape is described as Among them S α Convex hull contours that make up the shape; Step 9.2: Projection point set of each partition in turn Apply the Alpha shapes algorithm in step 9.1 to generate the corresponding contour curve Step 9.3: Using the Center Points of the Left Atrium and Left Ventricle Determine the starting and ending points of each group of points and then shape the Alpha curve of each partition Corrected to a linear point set Step 9.4: Apply cubic spline interpolation to the corrected linear point set, for Generate a uniform three-dimensional resampling point set, denoted as 10. The method for automatically measuring mitral valve leaflet length according to claim 9, characterized in that: In step 10, the distance between each point is calculated in sequence using the uniformly sampled point set: Among them, p i and p i+1 are two adjacent points in the same partition; Calculate the leaflet length of each partition in turn. For each partition, accumulate the distances between all points and calculate the corresponding leaflet length, specifically: Among them, L A1 , L A2 , L A3 Represents the leaflet lengths of the three divisions of the anterior leaflet of the mitral valve, L P1 , L P2 , L P3 Represents the leaflet lengths of the three divisions of the posterior mitral leaflet.

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