WO2022241613A1

WO2022241613A1 - Elbow joint flexion and extension three-dimensional motion analysis method and apparatus based on ct images

Info

Publication number: WO2022241613A1
Application number: PCT/CN2021/094106
Authority: WO
Inventors: 高永生; 郎国栋; 李光杨; 赵杰
Original assignee: 哈尔滨工业大学
Priority date: 2021-05-17
Filing date: 2021-05-17
Publication date: 2022-11-24
Also published as: CN113507890B; CN113507890A

Abstract

An elbow joint flexion and extension three-dimensional motion analysis method and apparatus based on CT images, and a computer device and a computer readable storage medium. The method comprises: obtaining multiple CT images of an elbow joint at different heights in at least one posture (S1); calculating to obtain a three-dimensional model of the elbow joint according to the obtained CT images, the three-dimensional model comprising a humerus model and an ulna model (S2); on the surface of the humerus model, determining a first space curve according to an intersecting line of two concave side surfaces of a humeral trochlear groove, and dividing the first space curve into two sections by a coronal plane of a human body structure; and on the surface of the ulna model, determining a second space curve according to an intersecting line of two convex side surfaces of an ulnar trochlear incisura (S3); and fixing the humerus model, rotating the ulna model, and in the rotation process, making the two sections of first space curve be simultaneously tangent to the second space curve all the time, and analyzing the elbow joint flexion and extension three-dimensional motion (S4). According to the present solution, the real three-dimensional motion mode of the elbow joint can be reflected.

Description

Method and device for three-dimensional motion analysis of elbow joint flexion and extension based on CT images

technical field

The invention relates to the technical field of biomedical engineering, in particular to a CT image-based three-dimensional motion analysis method and device for elbow joint flexion and extension, computer equipment, and a computer-readable storage medium.

Background technique

The elbow joint is a relatively complex compound joint in the human body, and its main movement is three-dimensional movement of flexion and extension. The sliding and transmission involved in this movement are related to the structure of the humerus and ulna of the elbow joint. Due to the existence of the carrying angle, the movement track of the ulna is not in the same plane as the humerus. It can be considered that the axis of the elbow joint changes all the time during the movement.

At present, in the field of exoskeleton research, the exoskeleton installed at the flexion and extension joints of the human body usually adopts a fixed axis of motion, ignoring the physiological structure of the human joints, which may easily cause the coordinated movement of the exoskeleton and the human body to be uneven. In the field of sports medicine and biomedical measurement, various techniques have been widely used in upper limb modeling research, including electromagnetic motion capture, mechanical motion capture and high-speed camera shooting. However, these methods are based on the assumption that the markers truly simulate the movement of the bones, and need to embed or fix the markers in the skin and bones, and these markers limit the actual movement of the joints to a certain extent, and the overall operation process is relatively complicated.

Therefore, in view of the problems of high complexity and inaccurate extraction results of the current method for studying the three-dimensional motion of elbow joint flexion and extension, a more effective method for analyzing elbow joint motion is needed.

Contents of the invention

The object of the present invention is to provide a method for analyzing the three-dimensional flexion and extension motion of the elbow joint without interfering with the actual joint motion.

In order to achieve the above object, the present invention provides a method for analyzing the three-dimensional motion of elbow joint flexion and extension based on CT images, comprising the following steps:

S1. Obtain multiple CT images of elbow joints at different heights in at least one posture;

S2. Calculate the three-dimensional model of the elbow joint according to the acquired CT image, including the humerus model and the ulna model;

S3. On the surface of the humerus model, the first space curve is determined by the intersection line of the two concave sides of the groove of the humerus trochlea, and the first space curve is divided into two sections by the coronal plane of the human body structure; The surface of the ulnar model, the second space curve is determined by the intersection line of the two convex sides of the ulnar trochlear notch;

S4. Fix the humerus model, rotate the ulna model, and during the rotation process, always make two sections of the first space curve tangent to the second space curve at the same time, and analyze the three-dimensional movement of elbow joint flexion and extension.

Preferably, the step S1 further includes performing noise reduction preprocessing on each acquired CT image, and performing image segmentation and edge extraction of the elbow joint area.

Preferably, in the step S2, when calculating the three-dimensional model of the elbow joint, multiple CT images of the same posture and different heights are superimposed in order of height and interpolated for calculation.

Preferably, if in the step S1, two or more CT images under two postures are acquired, in the step S2, when calculating the three-dimensional model of the elbow joint, multiple CT images of one posture and different heights are first The initial three-dimensional model is obtained by stacking and interpolating calculations according to the height order, and then the preliminary three-dimensional model is corrected according to the CT images of different postures.

Preferably, in the step S4, when the ulna model is rotated, the contact between the olecranon part of the ulna model and the olecranon fossa part of the humerus model, and the coronoid part of the ulna model and the The contact of the coronoid fossa of the humerus model serves as a limit for rotating the ulna model.

The present invention also provides a three-dimensional motion analysis device for elbow joint flexion and extension based on CT images, including:

An image module, configured to acquire multiple CT images at different heights of the elbow joint under at least one posture;

The modeling module is used to calculate the three-dimensional model of the elbow joint according to the obtained CT image, including the humerus model and the ulna model;

The curve module is used to determine the first space curve on the surface of the humerus model by the intersection line of the two concave sides of the humeral trochlear groove, and divide the first space curve into two sections with the coronal plane of the human body structure; On the surface of the ulnar model, the second space curve is determined by the intersection line of the two convex sides of the ulnar trochlear notch;

The simulation module is used to fix the humerus model, rotate the ulna model, and during the rotation process, always make the two segments of the first space curve tangent to the second space curve at the same time, and analyze the three-dimensional movement of elbow joint flexion and extension .

Preferably, the image module is further configured to perform noise reduction preprocessing on each acquired CT image, and perform image segmentation and edge extraction of the elbow joint area.

Preferably, when the simulation module rotates the ulna model, the contact between the olecranon part of the ulna model and the olecranon fossa part of the humerus model, and the coronoid part of the ulna model and the humerus model The contact of the coronoid fossa serves as a limit for rotating the ulnar model.

The present invention also provides a computer device, including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the above-mentioned three-dimensional movement of elbow joint flexion and extension based on CT images can be realized. The steps of the analysis method.

The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any one of the above-mentioned CT image-based three-dimensional motion analysis methods for elbow joint flexion and extension are implemented.

The above-mentioned technical scheme of the present invention has the following advantages: the present invention provides a kind of elbow joint flexion and extension three-dimensional movement analysis method and device, computer equipment, computer-readable storage medium based on CT image, the present invention is based on CT image (computerized tomography image) ) to reconstruct the three-dimensional model of the elbow joint skeleton, assemble the humeral trochlear groove of the humerus model and the ulnar trochlear notch of the ulna model, and determine the constraint conditions of the elbow joint movement, so as to realize the three-dimensional movement of the simulated elbow joint flexion and extension. The present invention abandons the method of studying complex joint motions with a fixed shaft, does not need to implant markers to assist measurement, does not interfere with actual joint activities, and provides technical support for reconstruction and analysis of the real three-dimensional motion trajectory of the elbow joint.

Description of drawings

Fig. 1 is a schematic diagram of steps of a three-dimensional motion analysis method for elbow joint flexion and extension based on CT images in an embodiment of the present invention;

Fig. 2 (a) shows a humerus model reconstructed by CT image three-dimensionally;

Fig. 2 (b) shows a ulnar model reconstructed by CT image three-dimensionally;

Fig. 3 shows the three-dimensional model of the elbow joint after the humerus model and the ulna model are assembled according to the constraints;

Fig. 4 is a schematic structural diagram of a three-dimensional motion analysis device for elbow joint flexion and extension based on CT images in an embodiment of the present invention.

In the figure: 100: image module; 200: modeling module; 300: curve module; 400: simulation module.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

As shown in Figures 1 to 3, a CT image-based three-dimensional motion analysis method for elbow joint flexion and extension provided by an embodiment of the present invention includes the following steps:

S1. Acquire multiple CT images of elbow joints at different heights in at least one posture.

In this step S1, a plurality of CT images of the same posture and different heights are obtained for the elbow joint area, so as to reconstruct the three-dimensional model of the elbow joint bone subsequently. The CT image data format is DICOM format. In order to ensure the accuracy of the reconstructed model, preferably, for elbow joint CT images at different heights when the human body is in a prone position, the thickness of the CT tomography is not greater than 2mm, and for other postures, the thickness of the tomography should be appropriately reduced.

S2. Calculate the three-dimensional model of the elbow joint according to the multiple CT images obtained in step S1, including the humerus model and the ulna model.

In this step S2, the humerus model can be a complete model of the humerus bone, or a partial model of the humerus bone, as shown in Figure 2(a), it is enough to ensure that the bones in the elbow joint area are complete; It can be a local model corresponding to the elbow joint area, as shown in Fig. 2(b).

Calculating the 3D model of the elbow joint, that is, using 3D reconstruction software (such as Minics software) to reconstruct the model from CT images, includes modeling, smoothing the surface of the model, re-meshing and other specific operations. For the 3D reconstruction technology, reference may be made to the prior art, which will not be repeated here.

S3. On the surface of the humerus model, the first space curve is determined by the intersecting line of the two concave sides of the humeral trochlea groove, and the first space curve is divided into two sections by the coronal plane of the human body structure; on the surface of the ulna model Above, the second spatial curve is determined by the intersection of the two convex sides of the trochlear notch.

For the real humerus bone, the structure of the trochlear is equivalent to a groove structure. In the humerus model, the humeral trochlear groove is formed by two concave sides intersecting at the bottom of the groove structure, and the position where the two concave sides intersect is also the line connecting the low points of the groove bottom of the humeral trochlear groove. For a real ulnar bone, the structure of the ulnar trochlea corresponds to a convex structure. In the ulnar model, the ulnar trochlear notch is formed by the intersection of two convex sides at the top of the convex structure. Both the first space curve and the second space curve are irregular curves, composed of multiple segments of straight lines and curve connections, and the center of curvature is not at a fixed point. The orientation qualifiers "bottom", "top", "low" and "high" in this part are all relative to the structure of the model itself, "bottom" and "low" are used to indicate the groove structure, and "top" and " High" is used to indicate a convex structure.

The coronal plane of the human body structure is a section that longitudinally cuts the human body into front and back parts along the left and right directions. The coronal plane divides the first space curve on the surface of the humerus model into two sections, one section is located at the front side, and the other section is located at the back side. Assemble the humeral trochlear groove of the humerus model and the ulnar trochlear notch of the ulna model to form a joint structure. The constraint condition when assembling the elbow joint, that is, assembling the humerus model and the ulna model is: make the two segments of the first space curve on the front side and the back side be tangent to the second space curve at the same time. The orientation qualifiers "left", "right", "front" and "rear" in this part are all relative to the structure of the human body.

Preferably, the starting point of the first space curve can be set as the lowest point of the olecranon fossa of the humerus model, that is, the point where the olecranon fossa is closest to the coronal plane, and the starting point of the first space curve can be set as the coronoid fossa of the humerus model The lowest point of the ulna, that is, the point where the coronoid fossa is closest to the coronal plane, the starting point of the second space curve can be set as the tip of the olecranon of the ulna model, and the stop point of the second space curve can be set as the coronoid of the ulna model cutting edge.

S4. Fix the humerus model, rotate the ulna model, and during the rotation process, that is, drag the ulna model to make the ulna model and the humerus model move relative to each other, keep the two first space curves in phase with the second space curve at the same time. Cut and analyze the three-dimensional movement of elbow joint flexion and extension.

When the first space curve and the second space curve have only one tangent point, the freedom of joints is too high, which will cause unexpected and unrealistic movements. When there are two tangent points, that is, the first space curve is tangent to the second space curve on the front side and the back side of the human body respectively, the degree of freedom of the joint is reduced, which is more in line with the real law of elbow joint motion. The ulna model moves relative to the humerus model under the assembly relationship and constraint conditions, which can reflect the real three-dimensional motion mode of the elbow joint, so as to analyze the motion trajectory of the elbow joint.

Considering the human body structure, the end faces of the humerus bone and the ulna bone at the joint are covered with a cartilage layer, and the cartilage layer is evenly distributed. Preferably, the first space curve and the second space curve can be set as lines with diameters, and the lines The diameter is preferably no more than 1mm, so as to be closer to the real elbow joint motion pattern.

Preferably, step S1 also includes performing denoising preprocessing on each of the acquired CT images, removing the influence of the photographing instrument on the elbow joint image, performing image segmentation and edge extraction of the elbow joint area, and making the outline of each bone clear, so as to obtain More accurate bone information improves the accuracy of 3D reconstruction models.

Preferably, in step S2, when calculating the three-dimensional model of the elbow joint based on the acquired CT images, multiple CT images of the same posture and different heights are superimposed in order of height and interpolated to calculate the humerus model and ulna model.

Further, if two or more CT images of the elbow joint in two or more postures are obtained in step S1, in step S2, when calculating the three-dimensional model of the elbow joint based on the obtained CT images, firstly, multiple A preliminary three-dimensional model is obtained by stacking and interpolating the CT images in order of height, and then correcting the preliminary three-dimensional model according to the CT images of different postures.

Preferably, in step S4, when rotating the ulna model, the contact between the olecranon part of the ulna model and the olecranon fossa part of the humerus model, and the contact between the coronoid part of the ulna model and the coronoid fossa part of the humerus model are regarded as rotation Limits for the ulna model. When simulating the flexion and extension of the elbow joint, the humerus model and the ulna model undergo relative sliding and transmission. When bending to the limit position, the coronoid part and the coronoid notch contact, so that the elbow joint can no longer bend and play a limiting role. When stretched to the limit position, the olecranon and the fossa of the olecranon are in contact, so that the elbow joint can no longer be extended, which acts as a limit, so as to better simulate the real three-dimensional movement mode of the elbow joint.

As shown in Figure 4, the present invention also provides a CT image-based three-dimensional motion analysis device for elbow joint flexion and extension, including an image module 100, a modeling module 200, a curve module 300 and a simulation module 400, specifically, wherein:

The image module 100 is used to acquire multiple CT images at different heights of the elbow joint under at least one posture;

The modeling module 200 is used to calculate the three-dimensional model of the elbow joint according to the obtained CT image, including the humerus model and the ulna model;

The curve module 300 is used to determine the first space curve on the surface of the humerus model by the intersecting line of the two concave sides of the trochlear groove, and divide the first space curve into two sections with the coronal plane of the human body structure; on the surface of the ulna model , the second space curve is determined by the intersection line of the two convex sides of the ulnar trochlear notch;

The simulation module 400 is used to fix the humerus model, rotate the ulna model, and during the rotation process, always make the two first space curves tangent to the second space curve at the same time, and analyze the three-dimensional movement of elbow joint flexion and extension.

Preferably, the image module 100 is further configured to perform noise reduction preprocessing on each acquired CT image, and perform image segmentation and edge extraction of the elbow joint area.

Preferably, when the modeling module 200 calculates the three-dimensional model of the elbow joint, multiple CT images of the same posture and different heights are superimposed in order of height, and interpolated.

Preferably, when the simulation module 400 rotates the ulna model, the contact between the olecranon part of the ulna model and the olecranon fossa part of the humerus model, and the contact between the coronoid part of the ulna model and the coronoid fossa part of the humerus model are regarded as rotating ulna. The limit of the model.

In particular, in some preferred embodiments of the present invention, a computer device is also provided, including a memory and a processor, the memory stores a computer program, and the processor implements any of the above-mentioned implementations when executing the computer program. The steps of the three-dimensional motion analysis method of elbow joint flexion and extension based on CT images described in the method.

In other preferred embodiments of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, the CT image-based elbow described in any of the above-mentioned embodiments is implemented. The steps of the three-dimensional motion analysis method for joint flexion and extension.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented through computer programs to instruct related hardware. The computer programs can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it may include the flow of the embodiment of the method for analyzing the three-dimensional motion of elbow joint flexion and extension based on CT images, and the description will not be repeated here.

In summary, the present invention provides a CT image-based elbow joint flexion and extension three-dimensional motion analysis method and device, computer equipment, and a computer-readable storage medium. The present invention reconstructs a three-dimensional model of the elbow bone based on the CT image, and through the humerus model The humeral trochlear groove and the ulnar trochlear notch of the ulna model are assembled to determine the constraint conditions of the elbow joint movement, which can realize the non-invasive analysis of the three-dimensional movement of the elbow joint flexion and extension, and reconstruct the real three-dimensional movement mode of the elbow joint.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent replacements are made to some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

A method for analyzing three-dimensional motion of elbow joint flexion and extension based on CT images, characterized in that it comprises the following steps:

S1. Obtain multiple CT images of elbow joints at different heights in at least one posture;

S2. Calculate the three-dimensional model of the elbow joint according to the acquired CT image, including the humerus model and the ulna model;

S3. On the surface of the humerus model, the first space curve is determined by the intersection line of the two concave sides of the groove of the humerus trochlea, and the first space curve is divided into two sections by the coronal plane of the human body structure; The surface of the ulnar model, the second space curve is determined by the intersection line of the two convex sides of the ulnar trochlear notch;

S4. Fix the humerus model, rotate the ulna model, and during the rotation process, always make two sections of the first space curve tangent to the second space curve at the same time, and analyze the three-dimensional movement of elbow joint flexion and extension.
The three-dimensional motion analysis method for elbow joint flexion and extension based on CT images according to claim 1, characterized in that:

The step S1 also includes performing noise reduction preprocessing on each acquired CT image, and performing image segmentation and edge extraction of the elbow joint area.
The three-dimensional motion analysis method for elbow joint flexion and extension based on CT images according to claim 1, characterized in that:

In the step S2, when calculating the three-dimensional model of the elbow joint, multiple CT images of the same posture and different heights are superimposed in order of height, and interpolated for calculation.
The three-dimensional motion analysis method for elbow joint flexion and extension based on CT images according to claim 3, characterized in that:

If in the step S1, CT images under two or more postures are obtained, in the step S2, when calculating the three-dimensional model of the elbow joint, firstly, multiple CT images of one posture and different heights are arranged in order of height The initial three-dimensional model is obtained by superposition and interpolation calculation, and then the preliminary three-dimensional model is corrected according to the CT images of different postures.
The three-dimensional motion analysis method for elbow joint flexion and extension based on CT images according to claim 1, characterized in that:

In the step S4, when the ulna model is rotated, the contact between the olecranon part of the ulna model and the olecranon fossa part of the humerus model, and the coronoid part of the ulna model and the olecranon part of the humerus model The contact of the coronoid fossa serves as a limit for rotating the ulnar model.
A three-dimensional motion analysis device for elbow joint flexion and extension based on CT images, characterized in that it includes:

An image module, configured to acquire multiple CT images at different heights of the elbow joint under at least one posture;

The modeling module is used to calculate the three-dimensional model of the elbow joint according to the obtained CT image, including the humerus model and the ulna model;

The curve module is used to determine the first space curve on the surface of the humerus model by the intersection line of the two concave sides of the humeral trochlear groove, and divide the first space curve into two sections with the coronal plane of the human body structure; On the surface of the ulnar model, the second space curve is determined by the intersection line of the two convex sides of the ulnar trochlear notch;

The simulation module is used to fix the humerus model, rotate the ulna model, and during the rotation process, always make the two segments of the first space curve tangent to the second space curve at the same time, and analyze the three-dimensional movement of elbow joint flexion and extension .
The three-dimensional motion analysis device for elbow joint flexion and extension based on CT images according to claim 6, characterized in that:

The image module is also used to perform denoising preprocessing on each acquired CT image, and perform image segmentation and edge extraction of the elbow joint area.
The three-dimensional motion analysis device for elbow joint flexion and extension based on CT images according to claim 6, characterized in that:

When the simulation module rotates the ulna model, the contact between the olecranon part of the ulna model and the olecranon fossa part of the humerus model, and the coronoid part of the ulna model and the coronoid process of the humerus model The contact of the socket serves as a limit for rotating the ulnar model.
A computer device, comprising a memory and a processor, the memory stores a computer program, wherein when the processor executes the computer program, the CT image-based elbow described in any one of claims 1 to 5 is realized. The steps of the three-dimensional motion analysis method for joint flexion and extension.
A computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the three-dimensional motion analysis of elbow joint flexion and extension based on CT images according to any one of claims 1 to 5 is realized method steps.