Pelvic floor ultrasound key muscle group function quantification system for vaginal laxity

Abstract

The present application relates to the technical field of medical data processing, in particular to a pelvic floor ultrasound key muscle group function quantification system for vaginal relaxation, comprising: a data preprocessing module, used for acquiring a gray image and a vertical pulling rate at each time; a feature point screening module, used for acquiring a pubic symphysis reference point; in a local area with the pubic symphysis reference point as the vertex, an active muscle bundle point and a passive fascia point are respectively acquired according to the vertical pulling rate and the edge gradient characteristics of the pixel points; a transfer cost analysis module, used for obtaining a force transmission impedance value between the active muscle bundle point and the passive fascia point according to the distance between the active muscle bundle point and the passive fascia point and the similarity of the mechanical simulation direction, combined with the vertical pulling rate; a pathological state judgment module, used for matching the active muscle bundle point and the passive fascia point to judge the pathological state of vaginal relaxation of the subject. The present application can effectively distinguish two core pathological states of pelvic floor tissue hidden tear and fascia relaxation.

Description

Technical Field

[0001] This invention relates to the field of medical data processing technology, specifically to a pelvic floor ultrasound-based quantitative system for key muscle group functions in patients with vaginal laxity. Background Technology

[0002] Pelvic floor ultrasound is a core imaging technique for clinically assessing female pelvic floor dysfunction. In the auxiliary diagnosis of vaginal laxity, transperineal two-dimensional ultrasound is routinely used to assess the functional status of the pelvic floor muscles by observing the morphological changes of the levator ani hiatus when the patient performs anal contraction. In actual clinical examination, when the patient performs anal contraction, the pelvic floor muscles exhibit a funnel-shaped contraction movement towards the head. This movement includes not only displacement within the two-dimensional pelvic floor plane but also a significant longitudinal motion component perpendicular to the imaging plane.

[0003] When the pelvic floor muscles contract rapidly upwards, the pelvic floor anatomy being observed deviates from the fixed imaging plane of the ultrasound probe. The probe cannot track the same tissue cross-section in real time, resulting in geometric projection deviation. This causes the ultrasound image to present a visual result that does not match the actual muscle contraction state, making it difficult to distinguish between the two completely different states: weak muscle contraction and high-energy muscle deviating from the observation plane. Therefore, current pelvic floor function assessments, relying solely on morphological measurement methods, cannot accurately identify the pathological state where muscle contraction kinetic energy and actual work are separated, thus failing to effectively differentiate between the two core pathological states of pelvic floor tissue occult tears and fascial laxity. Summary of the Invention

[0004] To address the technical problem that existing morphological measurement methods cannot effectively distinguish between the two core pathological states of pelvic floor tissue occult tears and fascial laxity, the present invention aims to provide a pelvic floor ultrasound-based quantitative system for key muscle group function in vaginal laxity. The specific technical solution adopted is as follows:

[0005] The data preprocessing module is used to acquire the ultrasound echo radio frequency signal at each moment of a single complete anal contraction movement of the subject in the two-dimensional pelvic floor plane. Based on the ultrasound echo radio frequency signal and the time neighborhood data feature distribution at each moment, the grayscale image at each moment and the vertical lifting rate corresponding to each pixel are determined.

[0006] The feature point filtering module is used to identify feature points based on the grayscale distribution in the grayscale image at each time moment and obtain the pubic symphysis reference point; in the local area with the pubic symphysis reference point as the vertex, active muscle bundle points and passive fascia points are obtained respectively based on the data distribution of the vertical lifting rate of the pixel points and the edge gradient features.

[0007] The transmission cost analysis module is used to obtain the force transmission impedance value between each active muscle bundle point and each passive fascia point based on the distance distribution between each active muscle bundle point and each passive fascia point and the similarity of the corresponding mechanical simulation direction, combined with the vertical lifting rate of each active muscle bundle point.

[0008] The pathological condition judgment module is used to match active muscle bundle points and passive fascia points according to the force transmission impedance value, and use the obtained matching points to judge the pathological condition of vaginal laxity in the examinee.

[0009] Preferably, the step of identifying feature points based on the grayscale distribution in the grayscale image at each time moment to obtain the pubic symphysis reference point specifically includes:

[0010] A shallow region within a preset range is obtained from the grayscale image, and a segmentation threshold is determined based on the preset percentile of the maximum grayscale value within the shallow region. Connected component extraction is performed on the pixels in the shallow region whose grayscale values ​​are greater than or equal to the segmentation threshold to obtain the pubic region. The geometric center of the pubic region corresponding to the maximum area in all pubic regions is taken as the reference point of the pubic symphysis.

[0011] Preferably, the step of obtaining active muscle bundle points and passive fascia points respectively within a local region with the pubic symphysis reference point as the vertex, based on the data distribution of the vertical lifting rate of the pixels and the edge gradient features, specifically includes:

[0012] Obtain a local region within a preset range with the pubic symphysis reference point as its vertex;

[0013] Based on the feature distribution of pixels in a local area whose vertical lifting rate meets the rate threshold requirement, active muscle bundle points are obtained.

[0014] Edge feature analysis is performed on pixels within a local area to extract skeleton lines, and pixels are uniformly collected along the skeleton lines as passive fascia points.

[0015] Preferably, the step of obtaining active muscle bundle points based on the feature distribution of pixels whose vertical lifting rate meets the rate threshold requirement within a local area specifically includes:

[0016] Feature pixels with a vertical lifting rate greater than or equal to a preset rate threshold are obtained within a local area. Connectivity analysis is performed on the feature pixels, and the centroid of each connected component in the analysis results is taken as the active muscle bundle point.

[0017] Preferably, the step of obtaining the force transmission impedance value between each active muscle bundle point and each passive fascia point based on the distance distribution between each active muscle bundle point and each passive fascia point, the similarity of the corresponding mechanical simulation direction, and the vertical lifting rate of each active muscle bundle point, specifically includes:

[0018] For any active muscle bundle point and any passive fascia point, the section offset penalty coefficient corresponding to the active muscle bundle point is determined based on the ratio of the vertical lifting rate of the active muscle bundle point to the maximum value of all vertical lifting rates.

[0019] The distance between the active muscle bundle point and the passive fascia point is obtained as the myofascial distance coefficient.

[0020] The traction direction deviation coefficient is obtained based on the deviation between the directional characteristics from the active muscle bundle point to the passive fascia point and the directional characteristics from the active muscle bundle point to the pubic symphysis reference point.

[0021] Based on the sectional offset penalty coefficient, myofascial distance coefficient, and traction direction deviation coefficient, the force transmission impedance value between any active muscle bundle point and any passive fascial point is determined.

[0022] Preferably, the step of obtaining the traction direction deviation coefficient based on the deviation between the directional characteristics from the active muscle bundle point to the passive fascia point and the directional characteristics from the active muscle bundle point to the pubic symphysis reference point specifically includes:

[0023] Specifically, the unit vector from the active muscle bundle point to the passive fascia point is used as the traction direction vector; the unit vector from the active muscle bundle point to the pubic symphysis reference point is used as the maintenance direction vector.

[0024] The traction direction deviation coefficient is determined based on the angular deviation between the traction direction vector and the maintenance direction vector.

[0025] Preferably, the step of matching active muscle bundle points and passive fascial points based on the force transmission impedance value, and using the obtained matching points to determine the pathological state of vaginal laxity in the examinee, specifically includes:

[0026] Based on the force transmission impedance value, active muscle bundle points and passive fascial points are matched, and successfully matched active muscle bundle points and passive fascial points are formed into traction matching point pairs; active muscle bundle points that do not belong to traction matching point pairs are regarded as ineffective contraction points.

[0027] The ineffective contraction energy coefficient is obtained based on the cumulative vertical lifting rate of all ineffective contraction points and the cumulative vertical lifting rate of all active muscle bundle points.

[0028] The traction path deviation angle is obtained by comparing the angle between the directional characteristics of the active muscle bundle point to the passive fascia point in the traction matching point alignment and the traction direction vector.

[0029] The pathological state of vaginal laxity in the examinee is determined based on the ineffective contraction energy coefficient and the deviation angle of the traction path.

[0030] Preferably, the step of obtaining the ineffective contraction energy coefficient based on the cumulative vertical lifting rate of all ineffective contraction points and the cumulative vertical lifting rate of all active muscle bundle points specifically includes:

[0031] The ratio between the sum of the vertical lifting rates of all ineffective contraction points and the sum of the vertical lifting rates of all active muscle bundle points is taken as the ineffective contraction energy coefficient.

[0032] Preferably, the step of obtaining the traction path deviation angle based on the angle between the directional characteristics of the active muscle bundle point to the passive fascia point in the traction matching point alignment and the traction direction vector specifically includes:

[0033] The unit vector pointing from the active muscle bundle point to the passive fascia point in the traction matching point pair is used as the actual connection vector of the traction matching point pair;

[0034] The mean angle between each actual connection vector and the traction direction vector is obtained and used as the traction path deviation angle.

[0035] Preferably, the step of determining the pathological state of vaginal laxity in the examinee based on the ineffective contraction energy coefficient and the deviation angle of the traction path specifically includes:

[0036] When the ineffective contraction energy coefficient is greater than or equal to the preset energy threshold, the pathological state of vaginal laxity is a ruptured state.

[0037] When the ineffective contraction energy coefficient is less than the preset energy threshold and the traction path deviation angle is greater than or equal to the preset deviation angle threshold, the pathological state of vaginal laxity is the laxity state.

[0038] When the ineffective contraction energy coefficient is less than the preset energy threshold and the traction path deviation angle is less than the preset deviation angle threshold, the pathological state of vaginal laxity is normal.

[0039] The embodiments of the present invention have at least the following beneficial effects:

[0040] This invention first acquires the ultrasound echo radio frequency signal of a single complete anal contraction action through a data preprocessing module, and generates grayscale images at each moment by combining the temporal neighborhood data feature distribution, preserving the acoustic features of the anatomical structure, and obtaining the pixel-level vertical lifting rate to quantify the vertical component of the three-dimensional contraction motion, thus constructing spatiotemporally aligned two-dimensional basic data.

[0041] Then, the feature point screening module analyzes and identifies the pubic symphysis reference point by analyzing the grayscale distribution characteristics of the grayscale image, establishes a unified anatomical coordinate system, and eliminates probe displacement interference. Then, the local functional area is delineated with the reference point as the vertex, and the muscle bundle points that actively contract are screened based on the pixel vertical lifting rate distribution to characterize the source of power. The passively stressed fascia points are extracted through edge gradient features to characterize the force transmission carrier.

[0042] Furthermore, the transmission cost analysis module constructs a force transmission impedance value by comprehensively considering the distance distribution between active muscle bundle points and passive fascia points (physical transmission basis), the similarity of mechanical simulation directions (anatomical direction constraints), and the vertical lifting rate of active muscle bundle points. This restores the true efficiency of force transmission between muscle and fascia, solving the problem that two-dimensional imaging cannot reflect three-dimensional transmission characteristics.

[0043] Finally, the pathological condition assessment module matches active muscle bundle points and passive fascial points using force transmission impedance values, ultimately transforming the quantified force transmission results into clinically interpretable pathological classifications, achieving precise differentiation between tears and laxity. This solves the problem that traditional morphological assessments cannot distinguish pathological mechanisms, outputting objective and accurate pathological classification results, and providing direct decision support for clinicians to formulate personalized treatment plans. Attached Figure Description

[0044] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the pelvic floor ultrasound key muscle group function quantification system for vaginal laxity provided by the present invention;

[0046] Figure 2 This is a flowchart of the steps of the pelvic floor ultrasound method for quantifying the function of key muscle groups in vaginal laxity provided by the present invention.

[0047] Figure 3 This is a schematic diagram of the feature point filtering module provided by the present invention. Detailed Implementation

[0048] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the pelvic floor ultrasound key muscle group function quantification system for vaginal laxity proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0050] The following description, in conjunction with the accompanying drawings, details the specific scheme of the pelvic floor ultrasound key muscle group function quantification system for vaginal laxity provided by this invention.

[0051] Please see Figure 1 The diagram shows a structural schematic of a pelvic floor ultrasound key muscle group function quantification system for vaginal laxity provided by an embodiment of the present invention. The system includes a data preprocessing module, a feature point screening module, a transfer cost analysis module, and a pathological state judgment module.

[0052] The data preprocessing module is used to acquire the ultrasound echo radio frequency signal at each moment in the two-dimensional pelvic floor plane during a single complete anal contraction movement of the subject. Based on the ultrasound echo radio frequency signal and the temporal neighborhood data feature distribution at each moment, the grayscale image at each moment and the vertical lifting rate corresponding to each pixel are determined.

[0053] First, in order to capture the functional performance of the pelvic floor muscles under extreme contraction, the system first needs to determine the radiofrequency data of the maximum contraction state. The instantaneous imaging data when the tissue's lifting motion rate in the direction perpendicular to the ultrasound imaging plane reaches the global maximum during the pelvic floor muscles' completion of the anal contraction action is the peak moment of the release of pelvic floor muscle contraction kinetic energy, which can most realistically reflect the extreme contraction ability of the pelvic floor muscles and the instantaneous mechanical response state of the myofascial system.

[0054] Specifically, the patient is placed in the lithotomy position, and the system uses a convex array ultrasound probe (center frequency set to 4-8 MHz) placed in the midsagittal plane of the perineum to acquire an ultrasound echo radio frequency sequence containing a single complete anal contraction movement of the patient. This sequence consists of several consecutive frames of radio frequency data, each frame containing raw acoustic information without logarithmic compression and beamforming, preserving speckle features for motion estimation.

[0055] In this system, the patient is placed in the lithotomy position, and the ultrasound probe is positioned in the midsagittal plane of the perineum. The probe's transmission and reception range defines a two-dimensional physical imaging plane, which can be defined as a two-dimensional pelvic floor plane. The horizontal X-axis is parallel to the perineal surface, and the depth Y-axis is perpendicular to the probe surface. This plane covers the core anatomical structures of the pelvic floor, such as the pubic symphysis, levator ani muscle, and fascia. The radio frequency signal is the tissue echo acoustic signal received by the probe, and each echo originates from a unique spatial location (X, Y) within this plane.

[0056] It should be understood that the ultrasound echo radio frequency signals at each moment during a single complete anal contraction movement are arranged in time sequence to form an ultrasound echo radio frequency sequence. One moment corresponds to one frame of ultrasound echo radio frequency signal. Each frame of ultrasound echo radio frequency signal in the sequence corresponds to the radio frequency echo amplitude at all physical position coordinates within the two-dimensional pelvic floor plane. The essence of one frame is an instantaneous, complete full-field scan of the aforementioned two-dimensional pelvic floor plane by the ultrasound probe (as opposed to the cross-frame dynamics of continuous scanning). The scanning process completes two key operations, transforming the continuous physical space and acoustic signals into discrete digital sampling points.

[0057] Next, this embodiment uses frames t and t+1 as examples to illustrate the analysis of data similarity between adjacent ultrasound echo radio frequency signals using a normalized cross-correlation algorithm. The relevant parameter settings for this algorithm include: the system sets a matching window of size 3λ×3λ (λ being the ultrasound length) within the target region of frame t. This window size selection ensures sufficient speckle features to guarantee unique matching while avoiding an excessively large window that could lead to inconsistent motion (significant differences in local motion during pelvic floor muscle contraction).

[0058] Using a normalized cross-correlation algorithm, the system traverses frames t and t+1 to find the corresponding matching coordinate point pairs under the two-dimensional pelvic floor planes with the highest similarity. In the coordinate point pair, the vector pointing from the coordinate point in frame t to the coordinate point in frame t+1 determines the position offset vector of the coordinate point in frame t+1 in the corresponding matching point pair. The Y-axis component of this position offset vector, that is, the component in the depth direction (i.e., the direction perpendicular to the probe surface), is extracted as the vertical displacement component of the coordinate point in frame t+1. The ratio of the vertical displacement component to the time interval between two adjacent moments is used as the vertical lifting rate of the coordinate point in frame t+1. The arithmetic mean of the vertical lifting rates of all positions in the corresponding frame at each moment is calculated to obtain the full-field average vertical rate of the corresponding frame at each moment. The ultrasound echo radio frequency signal corresponding to the maximum value of the full-field average vertical rate of all frames is marked as the maximum contraction frame.

[0059] It should be noted that the subsequent feature analysis in this embodiment mainly focuses on the ultrasound echo radio frequency signal under the maximum contraction frame. This frame excludes low kinetic energy interference during the muscle contraction initiation and relaxation phases, locks in the mechanical peak state of active pelvic floor muscle contraction, and becomes the only static benchmark for subsequent extraction of anatomical features and analysis of myofascial force transmission efficiency. This ensures that all dynamic and morphological analyses are based on the most representative moment of pelvic floor muscle contraction, avoiding the impact of cross-frame motion errors on the evaluation results.

[0060] Finally, using conventional beamforming and envelope detection techniques, the ultrasonic echo radio frequency signal of the maximum contraction frame is converted into the corresponding B-mode grayscale image. It should be understood that the normalized cross-correlation algorithm and conventional beamforming and envelope detection techniques are well-known technologies, and will only be briefly introduced here without further detail.

[0061] The feature point filtering module is used to identify feature points based on the grayscale distribution in the grayscale image at each time moment and obtain the pubic symphysis reference point; within the local area with the pubic symphysis reference point as the vertex, active muscle bundle points and passive fascia points are obtained respectively based on the data distribution of the vertical lifting rate of the pixel points and the edge gradient features.

[0062] The main purpose of this module is to accurately extract key anatomical features related to functional assessment from pelvic floor ultrasound information, and to establish a discretized model of active muscle bundles and passive fascia under a unified spatial benchmark, providing a precise anatomical basis for subsequent dynamic impedance analysis. Pelvic floor ultrasound images often exhibit overlapping anatomical structures and significant noise interference, and the functional correlation between key muscle groups and fascia depends on well-defined spatial locations; direct extraction can easily lead to feature confusion or localization errors.

[0063] Therefore, by extracting stable pubic symphysis reference points in the shallow region of grayscale images to establish a unified spatial reference, and then acquiring local regions to focus on functionally relevant anatomical ranges, active muscle bundle points are extracted to represent muscle bundle units with contractile function, and passive fascia points are extracted to represent fascial structures that transmit force. Ultimately, the precise separation and discretization of key anatomical features are achieved, laying the foundation for subsequent analysis of muscle-fascial force transmission relationships.

[0064] Specifically, such as Figure 3 As shown, the feature point selection module includes a reference point selection unit, a muscle bundle point selection unit, and a fascia point selection unit. It should be noted that all grayscale images mentioned in this module refer to the grayscale image corresponding to the maximum contraction frame in the aforementioned modules.

[0065] The reference point filtering unit is used to obtain a shallow region within a preset range in the grayscale image, determine a segmentation threshold based on the preset percentile of the maximum grayscale value in the shallow region, extract connected components from the pixels in the shallow region whose grayscale values ​​are greater than or equal to the segmentation threshold to obtain the pubic region, and take the geometric center of the pubic region corresponding to the maximum area in all pubic regions as the pubic symphysis reference point.

[0066] First, in a grayscale image, the position of each pixel corresponds to a position coordinate in a two-dimensional pelvic floor plane. The vertical coordinate of this position coordinate represents the depth, that is, with the perineal surface where the ultrasound probe is attached as the depth origin, the direction perpendicular to the probe surface and pointing into the human body is the depth direction, and its value corresponds to the vertical distance between the pelvic floor tissue and the probe attachment surface.

[0067] Based on this, the region formed by pixels with a depth less than or equal to a preset depth threshold in the grayscale image is defined as the shallow region. In this embodiment, the preset depth threshold is 30 mm. Thus, the shallow region represents the anatomical area where the pubic symphysis is located, which is less than or equal to 3 cm from the probe contact surface.

[0068] It should be noted that the core physical principle of ultrasound imaging is that the difference in acoustic impedance between different tissues will produce echo signals of different intensities. The pubic symphysis, as a bony hard tissue, has an acoustic impedance much greater than that of the surrounding soft tissues such as muscles and fascia. Therefore, it reflects a high-intensity echo signal in ultrasound images, appearing as a bright area on the image. This is an inherent acoustic physical property of bone tissue. Therefore, this embodiment uses an adaptive threshold segmentation method to extract the bright portion of the superficial region and locate the spatial origin of the pelvic floor anatomy.

[0069] As a concrete example, 70% of the maximum grayscale value in the shallow region is set as the segmentation threshold. Pixels in the shallow region with grayscale values ​​greater than or equal to the segmentation threshold are selected, and connected component analysis is performed on these pixels to determine the pubic region. It should be noted that connected component analysis is a well-known technique and will not be elaborated upon here.

[0070] Screening the pubic symphysis by identifying the largest pubic region is based on the physical spatial characteristics of pelvic floor anatomy. That is, the pubic symphysis is the only large-volume bony landmark in the anterior and superior part of the pelvic floor, and its physical space is much larger than other superficial hyperechoic tissues. This allows for the unique identification of the pubic symphysis and eliminates interference from other small hyperechoic tissues.

[0071] As a concrete example, the geometric center can be the centroid of the region. For instance, the centroid of the pubic region corresponding to the largest area in all pubic regions can be used as the reference point for the pubic symphysis. This ensures that all subsequent calculations of the spatial position, movement rate, and traction direction of muscle bundle points and fascia points have a unified and stable physical spatial reference, eliminating spatial coordinate drift errors caused by the relative displacement between the probe and the human body and the movement of pelvic floor tissues.

[0072] It should be noted that if the shallow region connected domain extraction fails and the pubic symphysis reference point cannot be obtained, the system will trigger adjacent frame feature tracking or switch to manual calibration mode to determine the reference point.

[0073] The muscle bundle point selection unit is used to obtain a local area within a preset range with the pubic symphysis reference point as the vertex; and to obtain active muscle bundle points based on the feature distribution of pixels in the local area whose vertical lifting rate meets the rate threshold requirement.

[0074] First, using the pubic symphysis reference point as the vertex and the depth direction of the probe scan line (that is, the negative Y-axis) as the central axis, a fan-shaped region with an angle of 90° is constructed as a local region.

[0075] The local area reflects the physical characteristics based on the pelvic floor anatomy and physiology and ultrasound imaging. Defining the effective physical space for pelvic floor function analysis can effectively eliminate interference from irrelevant tissue areas, allowing subsequent muscle bundle point extraction and dynamic analysis to focus on the anatomical areas directly related to pelvic floor contraction function. The local area precisely covers the core functional area of ​​pelvic floor contraction, namely the distribution area of ​​the levator ani muscle group (mainly the puborectalis muscle) behind and deep to the pubic symphysis. This area is the only effective anatomical space for the pelvic floor to generate contractile kinetic energy and achieve force transmission.

[0076] Then, feature pixels with a vertical lifting rate greater than or equal to a preset rate threshold are obtained in the local area. Connectivity analysis is performed on the feature pixels, and the centroid of each connected component in the analysis results is taken as the active muscle bundle point.

[0077] As a concrete example, the rate threshold can be set to 1.5 times the arithmetic mean of the vertical lifting rates of all pixels within a local region. The connected regions containing pixels with high vertical rates correspond to the muscle bundles in the pelvic floor muscles that actually generate active contraction and release kinetic energy. By filtering pixels using the rate threshold, regions of muscle fibers with no or low contraction are excluded, thus achieving a physical distinction between functionally effective muscle bundles and functionally ineffective muscle tissue. Therefore, the active muscle bundle points characterize the contractile dynamics of the muscle bundle portion and belong to the force source characteristic points of force transmission in the myofascial system.

[0078] The fascia point screening unit is used to perform edge feature analysis on pixels in a local area to extract skeleton lines, and uniformly collect pixels on the skeleton lines as passive fascia points.

[0079] Specifically, morphological operations are performed on pixels within a local region to extract the skeleton lines of that region. Equal-interval sampling is then performed along these skeleton lines, and these points are defined as passive fascia points. The sampling interval can be 3 pixels. The method for skeleton line extraction is a well-known image processing technique and will not be elaborated upon here. For example, the morphological gradient of a local region in a grayscale image (dilation image minus erosion image) is calculated to enhance the edge features of the tissue interface. Then, a non-maximum suppression algorithm is applied to the gradient map to refine the tissue interface skeleton lines to a single pixel width.

[0080] The pelvic floor fascia, as the connective tissue between muscles and organs, is the passive force carrier of pelvic floor muscle contraction. In ultrasound radiofrequency data, it appears as an interface of abrupt acoustic impedance change between muscles and surrounding tissues, reflected as a high-contrast tissue edge in B-mode grayscale images. Enhancing this edge feature by calculating morphological gradients (expansion-reduction erosion) essentially utilizes the impedance difference principle of ultrasound to precisely separate the fascia's anatomical boundary from the complex pelvic floor tissue background, eliminating acoustic signal interference from muscles, organs, and other tissues, and restoring the true anatomical contour of the fascia.

[0081] The non-maximum suppression algorithm is applied to the morphological gradient map to refine the tissue interface skeleton line with a width of one pixel. Its physical significance is to remove redundant pixel information in the edge area while preserving the core geometric features of the fascial anatomical boundary, so as to achieve accurate and one-dimensional extraction of the fascial boundary.

[0082] Thus, passive fascial points characterize the features of passively stressed connective tissues such as the pelvic floor fascia, and belong to the load-bearing end features of force transmission in the muscle-fascia system.

[0083] The transmission cost analysis module is used to obtain the force transmission impedance value between each active muscle bundle point and each passive fascia point based on the distance distribution between each active muscle bundle point and each passive fascia point, the similarity of the corresponding mechanical simulation direction, and the vertical lifting rate of each active muscle bundle point.

[0084] The main purpose of this module is to construct a force transmission impedance model that integrates geometric distance, mechanical direction, and three-dimensional motion characteristics. This model accurately quantifies the difficulty of force transmission between active muscle bundles and passive fascia, providing a core basis for subsequent determination of the effectiveness of muscle-fascia connections. Two-dimensional ultrasound imaging cannot fully reproduce the three-dimensional characteristics of pelvic floor muscle contraction. Relying solely on distance or direction cannot reflect the true force transmission efficiency. In other words, even if a rapidly shifting muscle bundle point is close to a fascial point, the actual transmission effect will be significantly attenuated, and non-physiological traction will increase transmission resistance.

[0085] Therefore, this module first calculates the planar Euclidean distance between each active muscle bundle point and passive fascia point (characterizing the physical basis of conduction); then, by comparing the similarity between the actual traction direction and the anatomical guide vector of the muscle fibers, a direction deviation factor is generated (penalizing traction in non-physiological directions); finally, a section loss penalty factor is constructed by combining the vertical lifting rate of the active muscle bundle point (quantifying the attenuation effect of the offset on conduction). Multiplying the three factors together yields the force transmission impedance value. The smaller the impedance value, the smoother the force transmission, and vice versa. Thus, the true state of three-dimensional muscle-fascia force transmission is accurately reproduced in two-dimensional data.

[0086] The first step is to determine the sectional offset penalty coefficient corresponding to any active muscle bundle point and any passive fascia point based on the ratio of the vertical lifting rate of the active muscle bundle point to the maximum value of all vertical lifting rates.

[0087] The penalty coefficient is constructed based on the ratio of the vertical lifting rate of the active muscle bundle point to the maximum vertical lifting rate of all muscle bundle points. It is usually a monotonically increasing function of this ratio, such as linear or non-linear weighting.

[0088] As a concrete example, taking any active muscle fasciculus point as an illustration, the method for obtaining the sectional offset penalty coefficient corresponding to the nth active muscle fasciculus point can be expressed by the formula:

[0089]

[0090] in, This represents the tangential offset penalty coefficient corresponding to the nth active muscle fasciculus point. This represents the vertical lifting rate of the nth active muscle fasciculus. This represents the maximum value of all vertical lifting rates.

[0091] The sectional offset penalty coefficient is a weight that characterizes the difficulty of connection. Essentially, it converts the vertical escape velocity of active muscle bundle points into impedance gain of in-plane force transmission. Its core function is to make the algorithm pay a higher price when matching passive fascia points for active muscle bundle points that run fast and have a greater degree of offset.

[0092] When the basal muscles contract, they pull upwards. The faster the vertical movement speed of some active muscle bundles, the more prone they are to displacement. In this case, even if a passive fascia point can be found in the plane, the actual force transmission efficiency will be greatly reduced, or even unable to effectively stretch. The higher the vertical lifting speed, the larger the value of the sectional displacement penalty coefficient, and the higher the cost of force transmission between active muscle bundles and passive fascia points. The more likely the algorithm is to determine that the active muscle bundle cannot establish an effective connection, and ultimately classify it as an anchored muscle bundle. This restores the true muscle-fascia force transmission state and avoids the algorithm mistakenly matching escaped high-kinetic-energy muscle bundles to fascia points in the plane.

[0093] It should be noted that if the subject's pelvic floor muscles show no contraction (e.g., severe muscle weakness), the vertical lifting rate of all pixels will be 0, and the global maximum value will be [not specified]. Direct calculation with 0 will result in a division error in the denominator. Adding a very small positive number to the denominator, such as 0.001, can prevent program crashes and the inability to calculate the penalty coefficient.

[0094] The second step is to obtain the distance between the active muscle bundle point and the passive fascia point as the myofascial distance coefficient.

[0095] Specifically, the Euclidean distance between the active muscle bundle points and the passive fascia points is calculated using the coordinate values ​​of the active muscle bundle points and the passive fascia points in the grayscale image, and the corresponding myofascial distance coefficients are obtained.

[0096] The closer the myofascial point is, the shorter the force transmission path and the less loss, the myofascial distance coefficient approaches 0, and the low impedance contribution; the farther the myofascial point is, the longer the force transmission path and the greater the loss, the myofascial distance coefficient approaches 1, and the high impedance contribution, which is consistent with the basic law in mechanics that contact force or tension decreases with the transmission distance.

[0097] The third step is to obtain the traction direction deviation coefficient based on the deviation between the directional characteristics of the active muscle bundle point to the passive fascia point and the directional characteristics of the active muscle bundle point to the pubic symphysis reference point.

[0098] Specifically, the unit vector from the active muscle bundle point to the passive fascia point is used as the traction direction vector; the unit vector from the active muscle bundle point to the pubic symphysis reference point is used as the maintenance direction vector; and the traction direction deviation coefficient is determined based on the angular deviation between the traction direction vector and the maintenance direction vector.

[0099] It should be noted that when the active muscle bundle point and the passive fascia point coincide, the traction direction vector is set to zero. The active muscle bundle point of the pelvic floor muscles is the force source end, and the passive fascia point is the load end. Their coincidence means that the muscle bundle and fascia overlap at the pixel level, with no actual force transmission path. In this case, the traction direction has no physiological significance. When the active muscle bundle point coincides with the pubic symphysis reference point, the maintenance direction vector is set to zero. The pubic symphysis reference point is the spatial origin of pelvic floor anatomy. The coincidence of the active muscle bundle point and the reference point indicates that the muscle bundle point is located in the bony region of the pubic symphysis (the hard tissue in the anterior and superior part of the pelvic floor). However, there are no functional pelvic floor contractile muscle bundles in the pubic symphysis region (pelvic floor contractile muscle bundles are mainly distributed behind or deep to the pubic symphysis). This feature point belongs to the pseudo muscle bundle point selected by the algorithm and is not a real active contractile muscle bundle.

[0100] As a concrete example, taking any active muscle bundle point and any passive fascia point as an illustration, the method for obtaining the traction direction deviation coefficient corresponding to the nth active muscle bundle point and the mth passive fascia point can be expressed as follows:

[0101]

[0102] in, This represents the deviation coefficient of the traction direction between the nth active muscle bundle point and the mth passive fascia point. This represents the traction direction vector corresponding to the nth active muscle fasciculus point and the mth passive fascia point. Let represent the maintenance direction vector corresponding to the nth active muscle fasciculus point and the pubic symphysis reference point, where n represents the nth active muscle fasciculus point, m represents the mth passive fasciculus point, G represents the pubic symphysis reference point, and exp represents an exponential function with the natural constant e as the base.

[0103] This indicates that the dot product of two vectors results in the cosine of the angle between them, with a range of [-1, 1]. The traction direction deviation coefficient is essentially a directional consistency reward function (reverse penalty). This term ensures that when the actual traction direction aligns with the anatomical force line, the traction direction deviation coefficient is 1, minimizing the cost. As the deviation angle increases, the cost rises exponentially, thus suppressing the interpretation of reverse or lateral pathological connections.

[0104] If the angle between the two vectors is 0° (the directions are completely consistent), it means that the direction of muscle fascia traction conforms to the physiological trajectory, the effective component of force transmission is the largest, and the deviation coefficient of traction direction is smaller; if the angle approaches 90° (the direction is seriously deviated), it means that most of the component of muscle fascia contraction force cannot be transmitted to the fascia point, the ineffective loss is large, and the deviation coefficient of traction direction is larger (high impedance contribution).

[0105] It should be understood that the magnitude of both the traction direction vector and the maintenance direction vector is 1, and both are vectors representing direction.

[0106] The fourth step is to determine the force transmission impedance value between any active muscle bundle point and any passive fascia point based on the sectional offset penalty coefficient, myofascial distance coefficient, and traction direction deviation coefficient.

[0107] Specifically, the product of the sectional offset penalty coefficient, the myofascial distance coefficient, and the traction direction deviation coefficient is used as the force transmission impedance value between the active muscle bundle point and the passive fascial point.

[0108] Using the same analytical method, the corresponding force transmission impedance value can be calculated for each active muscle bundle point and each passive fascial point. The limiting factors of pelvic floor muscle-fascial force transmission have a multiplicative effect; that is, the three types of physical factors hindering force transmission are mutually coupled and amplified step by step, and the product form better reflects the physical nature of force transmission loss. The force transmission impedance value is a quantitative indicator of the comprehensive degree of resistance generated by the combined coupling of offset interference, spatial distance attenuation, and traction direction deviation during the transmission of contractile force from the active muscle bundle point to the passive fascial point. A higher value indicates lower force transmission efficiency between the muscle and fascia, and vice versa. In other words, the force transmission impedance value quantifies the comprehensive degree of force transmission resistance between muscle-fascial point pairs, reflecting the force transmission efficiency inversely.

[0109] The pathological condition judgment module is used to match active muscle bundle points and passive fascia points according to the force transmission impedance value, and use the obtained matching points to judge the pathological condition of vaginal laxity in the examinee.

[0110] The main purpose of this module is to transform the quantitative results of force transmission impedance into accurate pathological judgment criteria. Through optimal matching and dual-dimensional index calculation, it enables the independent differentiation of two pathological mechanisms in vaginal laxity: muscle fiber tearing and fascial laxity, providing objective data support for clinical classification.

[0111] Previously, impedance values ​​alone could not directly correlate with pathological states, and it was necessary to avoid confusing ineffective contraction (tear) with path deviation (laxity). Simple morphological observation was insufficient to quantify these two latent lesions. Therefore, based on the force transmission impedance value, a global optimization matching algorithm was used to find the traction matching point pair (effective connection) with the minimum total cost. Unmatched active muscle bundle points were defined as ineffective contraction points (corresponding to failure of muscle-fascia connection). Then, the ineffective contraction energy coefficient (quantifying the degree of latent tear) was calculated by the cumulative ratio of the vertical lifting rate of the ineffective contraction point to all active muscle bundle points. Subsequently, the angle between the actual direction and the ideal traction direction of the traction matching point pair was extracted to obtain the traction path deviation angle (quantifying the degree of fascial laxity). Finally, the numerical range of two orthogonal indices was combined to comprehensively determine whether the subject was tear-dominant, laxity-dominant, or functionally intact, achieving a precise transformation from mechanical quantification to clinical diagnosis and solving the pain point of difficulty in distinguishing pathological mechanisms in traditional assessment.

[0112] The first step is to match active muscle bundle points and passive fascial points based on the force transmission impedance value, and obtain successfully matched active muscle bundle points and passive fascial points to form traction matching point pairs; active muscle bundle points that do not belong to traction matching point pairs are regarded as ineffective contraction points.

[0113] As a specific example, when the force transmission impedance between the active muscle bundle point and the passive fascia point is less than or equal to a preset connection threshold, the active muscle bundle point and the passive fascia point are formed into a traction matching point pair; when the force transmission impedance between the active muscle bundle point and the passive fascia point is greater than the preset connection threshold, the active muscle bundle point is regarded as an ineffective contraction point.

[0114] One approach is to set 10% of the diagonal length of the local region corresponding to the active muscle bundle point as the connection threshold, representing the physiological limit of connectivity.

[0115] The essential characteristic of ineffective contraction points is a high vertical lifting rate, but due to misalignment, they cannot find a matching fascial point within a physiologically reasonable distance. Pathologically, this corresponds to the "idling" phenomenon where muscle fibers, although generating strong contractions, cannot drive vaginal wall movement due to broken connection structures—a condition known as occult tearing. In other words, ineffective contraction points represent active muscle bundles possessing active contractile kinetic energy but unable to establish an effective force transmission connection with passive fascial points due to muscle-fascial connection failure, thus remaining in a high-energy idle state. This is a core characteristic of structural connection failures such as occult tears in the pelvic floor muscles.

[0116] The traction matching point pair is a combination of points whose force transmission impedance values ​​between active muscle bundle points and passive fascial points meet the physiological limit threshold and can achieve effective transmission of contractile force. It is a direct indication that the force transmission path of the myofascial system is unobstructed and that it has normal traction work function.

[0117] The second step is to obtain the ineffective contraction energy coefficient based on the cumulative vertical lifting rate of all ineffective contraction points and the cumulative vertical lifting rate of all active muscle bundle points.

[0118] Specifically, the ratio between the sum of the vertical lifting rates of all ineffective contraction points and the sum of the vertical lifting rates of all active muscle bundle points is used as the ineffective contraction energy coefficient.

[0119] The ineffective contraction energy coefficient directly reflects the proportion of muscle contraction energy that fails to be converted into effective stretching work. The dynamic characteristics of local ineffective contraction points are integrated into a global quantitative indicator of structural damage.

[0120] The ineffective contraction energy coefficient characterizes the severity of occult tears in the pelvic floor muscles. The larger the ineffective contraction energy coefficient, the greater the proportion of kinetic energy generated by pelvic floor muscle contraction that is dissipated due to structural connection failure, and the more severe the structural damage to the myofascial system. The smaller the ineffective contraction energy coefficient, the higher the proportion of kinetic energy of muscle bundle contraction that can be effectively converted into force transmission, and the better the structural integrity of the pelvic floor muscles.

[0121] It should be noted that if the subject's pelvic floor muscles do not contract at all, or if all active muscle bundle points are effectively matched, a division-by-zero error will occur. Furthermore, if the values ​​are consistently extremely small (e.g., extremely weak muscle strength), the ratio will be abnormally amplified, leading to distorted indicators. Therefore, a very small positive number, such as 0.001, is added to the denominator when calculating the ineffective contraction energy coefficient to avoid incomprehensibility.

[0122] The third step is to obtain the traction path deviation angle based on the angle between the directional characteristics of the active muscle bundle point to the passive fascia point in the traction matching point and the traction direction vector.

[0123] Specifically, the unit vector pointing from the active muscle bundle point to the passive fascia point in the traction matching point pair is taken as the actual connection vector of the traction matching point pair; the mean value of the angle between each actual connection vector and the traction direction vector is obtained as the traction path deviation angle.

[0124] The traction path deviation angle characterizes the degree of functional relaxation of the fascia caused by overstretching within the effective force transmission range.

[0125] The ideal traction direction is along the physiological force line of pelvic floor muscle contraction. However, as a connective tissue for force transmission, the fascia's ability to restrain muscle contraction decreases if it becomes lax, causing the actual traction path to deviate from the physiological force line, resulting in an angular deviation. Therefore, the magnitude of this deviation angle is positively correlated with the degree of laxity of the pelvic floor fascia. A larger deviation angle indicates a more significant deviation of the effective force transmission path from the ideal physiological trajectory, and more severe functional laxity of the fascia due to overstretching. Conversely, a smaller deviation angle indicates a stronger restraining ability of the fascia to transmit force, maintaining muscle contraction along the physiological force line, and more normal fascial function.

[0126] The fourth step is to determine the pathological state of vaginal laxity in the examinee based on the ineffective contraction energy coefficient and the deviation angle of the traction path.

[0127] When the ineffective contraction energy coefficient is greater than or equal to the preset energy threshold, the pathological state of vaginal laxity is a ruptured state.

[0128] The ineffective contraction energy coefficient is used as the primary criterion because structural tears (occult muscle fiber ruptures) are a more fundamental form of pelvic floor dysfunction than functional laxity. If the myofascial system has failed to maintain structural connections, even without significant fascial laxity, the core force transmission mechanism of the pelvic floor has been disrupted. Therefore, when the ineffective contraction energy coefficient exceeds the clinical threshold, regardless of the angle of deviation in the traction path, it is classified as a tear-dominated type.

[0129] When the ineffective contraction energy coefficient is less than the preset energy threshold, and the traction path deviation angle is greater than or equal to the preset deviation angle threshold, the pathological state of vaginal laxity is a relaxed state. When the ineffective contraction energy coefficient is less than the preset energy threshold, and the traction path deviation angle is less than the preset deviation angle threshold, the pathological state of vaginal laxity is a normal state.

[0130] Only when the ineffective contraction energy coefficient does not exceed the threshold, i.e. the pelvic floor muscle-fascia structure is intact and there is no significant hidden tear, the traction path deviation angle is used as the criterion. If the traction path deviation angle exceeds the deviation angle threshold, it indicates that the core cause of pelvic floor dysfunction is the force transmission path deviation caused by excessive fascia extension, and it is judged as the relaxation-dominant type. If both indicators do not exceed the threshold, it indicates that the pelvic floor muscle structure is intact, the fascia's force transmission constraint function is normal, and the muscle-fascia system can achieve efficient force transmission, and it is judged as the functionally intact type.

[0131] It should be noted that the pathological state of vaginal laxity determined in the embodiments of the present invention refers to the classification of the mechanical connection state of the pelvic floor muscle-fascia system. It can serve as an auxiliary judgment guide for clinical assessment of pelvic floor function and formulation of targeted intervention plans. It can provide reference guidance for medical staff to judge the type and degree of pelvic floor function damage in examinees and help improve the logic of clinical assessment.

[0132] In this embodiment, the deviation angle threshold is set at 0.3 radians, approximately equal to 17 degrees. Anatomically, the angle between the ideal contraction line of the puborectalis muscle and the actual traction path is nearly parallel in healthy individuals. When the deviation angle exceeds 17 degrees, it indicates significant anatomical displacement or compensatory torsion of the tissue. This value is clinically calibrated and corresponds to the critical point of nonlinear traction caused by decreased fascial tension. In practical applications of other embodiments, the value can be fine-tuned according to the tissue elasticity constant of subjects of different ages, typically ranging from [0.2, 0.5] radians.

[0133] In this embodiment, the energy threshold is set to 0.2, which is defined as the critical percentage of ineffective dissipated kinetic energy to total contractile kinetic energy, i.e., 20%. When more than 20% of the contractile kinetic energy fails to be transferred to the fascial load through effective connection, the system determines it as a occult tear.

[0134] It should be understood that both the deviation angle threshold and the energy threshold are empirical values ​​obtained through statistical calibration based on a database of known clinical cases. It should be noted that the thresholds set in these embodiments are empirical reference values ​​based on historical ultrasound image samples. In practical applications, they can be adaptively fine-tuned by considering the patient's age and tissue elasticity parameters.

[0135] In some embodiments, the pelvic floor ultrasound key muscle group function quantification system for vaginal laxity provided by the present invention is also used to implement the steps of the pelvic floor ultrasound key muscle group function quantification method for vaginal laxity.

[0136] Please see Figure 2 The diagram illustrates a flowchart of a method for quantifying the function of key pelvic floor muscle groups using ultrasound for vaginal laxity, according to an embodiment of the present invention. The method includes the following steps:

[0137] Step S100: Acquire the ultrasound echo radio frequency signal at each moment of a single complete anal contraction movement of the subject in the two-dimensional pelvic floor plane. Based on the ultrasound echo radio frequency signal and the time neighborhood data feature distribution at each moment, determine the grayscale image at each moment and the vertical lifting rate corresponding to each pixel.

[0138] Step S200: Feature point identification is performed based on the grayscale distribution in the grayscale image at each time point to obtain the pubic symphysis reference point; in the local area with the pubic symphysis reference point as the vertex, active muscle bundle points and passive fascia points are obtained respectively based on the data distribution of the vertical lifting rate of the pixel points and the edge gradient features.

[0139] Step S300: Based on the distance distribution between each active muscle bundle point and each passive fascia point and the similarity of the corresponding mechanical simulation direction, and combined with the vertical lifting rate of each active muscle bundle point, the force transmission impedance value between each active muscle bundle point and each passive fascia point is obtained.

[0140] Step S400: Match the active muscle bundle points and passive fascia points according to the force transmission impedance value, and use the obtained matching points to determine the pathological state of vaginal laxity in the examinee.

[0141] Since the system implementation has already been described in detail, it will not be repeated here.

[0142] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A pelvic floor ultrasound-based quantitative system for key muscle group function in treating vaginal laxity, characterized in that: The system includes: The data preprocessing module is used to acquire the ultrasound echo radio frequency signal at each moment of a single complete anal contraction movement of the subject in the two-dimensional pelvic floor plane. Based on the ultrasound echo radio frequency signal and the time neighborhood data feature distribution at each moment, the grayscale image at each moment and the vertical lifting rate corresponding to each pixel are determined. The feature point filtering module is used to identify feature points based on the grayscale distribution in the grayscale image at each time moment and obtain the pubic symphysis reference point; in the local area with the pubic symphysis reference point as the vertex, active muscle bundle points and passive fascia points are obtained respectively based on the data distribution of the vertical lifting rate of the pixel points and the edge gradient features. The transmission cost analysis module is used to obtain the force transmission impedance value between each active muscle bundle point and each passive fascia point based on the distance distribution between each active muscle bundle point and each passive fascia point and the similarity of the corresponding mechanical simulation direction, combined with the vertical lifting rate of each active muscle bundle point. The pathological condition judgment module is used to match active muscle bundle points and passive fascia points according to the force transmission impedance value, and use the obtained matching points to judge the pathological condition of vaginal laxity in the examinee.

2. The pelvic floor ultrasound-based quantitative system for key muscle group function in treating vaginal laxity according to claim 1, characterized in that, The step of identifying feature points based on the grayscale distribution in the grayscale image at each time moment to obtain the pubic symphysis reference point specifically includes: A shallow region within a preset range is obtained from the grayscale image, and a segmentation threshold is determined based on the preset percentile of the maximum grayscale value within the shallow region. Connected component extraction is performed on the pixels in the shallow region whose grayscale values ​​are greater than or equal to the segmentation threshold to obtain the pubic region. The geometric center of the pubic region corresponding to the maximum area in all pubic regions is taken as the reference point of the pubic symphysis.

3. The pelvic floor ultrasound-based quantitative system for key muscle group function in treating vaginal laxity according to claim 1, characterized in that, Within a local region with the pubic symphysis as the apex, active muscle bundle points and passive fascia points are obtained based on the data distribution of the vertical lifting rate of pixels and edge gradient features, specifically including: Obtain a local region within a preset range with the pubic symphysis reference point as its vertex; Based on the feature distribution of pixels in a local area whose vertical lifting rate meets the rate threshold requirement, active muscle bundle points are obtained. Edge feature analysis is performed on pixels within a local area to extract skeleton lines, and pixels are uniformly collected along the skeleton lines as passive fascia points.

4. The pelvic floor ultrasound-based quantitative system for key muscle group function in treating vaginal laxity according to claim 3, characterized in that, The step of obtaining active muscle bundle points based on the feature distribution of pixels whose vertical lifting rate meets the rate threshold requirement within a local area specifically includes: Feature pixels with a vertical lifting rate greater than or equal to a preset rate threshold are obtained within a local area. Connectivity analysis is performed on the feature pixels, and the centroid of each connected component in the analysis results is taken as the active muscle bundle point.

5. The pelvic floor ultrasound-based quantitative system for key muscle group function in treating vaginal laxity according to claim 1, characterized in that, The method involves obtaining the force transmission impedance value between each active muscle bundle point and each passive fascia point based on the distance distribution between each active muscle bundle point and each passive fascia point, the similarity of the corresponding mechanical simulation direction, and the vertical lifting rate of each active muscle bundle point. Specifically, this includes: For any active muscle bundle point and any passive fascia point, the section offset penalty coefficient corresponding to the active muscle bundle point is determined based on the ratio of the vertical lifting rate of the active muscle bundle point to the maximum value of all vertical lifting rates. The distance between the active muscle bundle point and the passive fascia point is obtained as the myofascial distance coefficient. The traction direction deviation coefficient is obtained based on the deviation between the directional characteristics from the active muscle bundle point to the passive fascia point and the directional characteristics from the active muscle bundle point to the pubic symphysis reference point. Based on the sectional offset penalty coefficient, myofascial distance coefficient, and traction direction deviation coefficient, the force transmission impedance value between any active muscle bundle point and any passive fascial point is determined.

6. The pelvic floor ultrasound key muscle group function quantification system for vaginal laxity according to claim 5, characterized in that, The traction direction deviation coefficient is obtained based on the deviation between the directional characteristics from the active muscle bundle point to the passive fascia point and the directional characteristics from the active muscle bundle point to the pubic symphysis reference point. Specifically, this includes: Specifically, the unit vector from the active muscle bundle point to the passive fascia point is used as the traction direction vector; the unit vector from the active muscle bundle point to the pubic symphysis reference point is used as the maintenance direction vector. The traction direction deviation coefficient is determined based on the angular deviation between the traction direction vector and the maintenance direction vector.

7. The pelvic floor ultrasound key muscle group function quantification system for vaginal laxity according to claim 6, characterized in that, The matching of active muscle bundle points and passive fascial points based on the force transmission impedance value, and the use of the obtained matching points to determine the pathological state of vaginal laxity in the examinee, specifically includes: Based on the force transmission impedance value, active muscle bundle points and passive fascial points are matched, and successfully matched active muscle bundle points and passive fascial points are formed into traction matching point pairs; active muscle bundle points that do not belong to traction matching point pairs are regarded as ineffective contraction points. The ineffective contraction energy coefficient is obtained based on the cumulative vertical lifting rate of all ineffective contraction points and the cumulative vertical lifting rate of all active muscle bundle points. The traction path deviation angle is obtained by comparing the angle between the directional characteristics of the active muscle bundle point to the passive fascia point in the traction matching point alignment and the traction direction vector. The pathological state of vaginal laxity in the examinee is determined based on the ineffective contraction energy coefficient and the deviation angle of the traction path.

8. The pelvic floor ultrasound-guided functional quantification system for key muscle groups in vaginal laxity according to claim 7, characterized in that, The ineffective contraction energy coefficient is obtained based on the cumulative vertical lifting rates of all ineffective contraction points and the cumulative vertical lifting rates of all active muscle bundle points. Specifically, this includes: The ratio between the sum of the vertical lifting rates of all ineffective contraction points and the sum of the vertical lifting rates of all active muscle bundle points is taken as the ineffective contraction energy coefficient.

9. The pelvic floor ultrasound-based quantitative system for key muscle group function in treating vaginal laxity according to claim 7, characterized in that, The traction path deviation angle is obtained by calculating the angle between the directional characteristics of the active muscle bundle point to the passive fascia point in the traction matching point alignment and the traction direction vector. Specifically, this includes: The unit vector pointing from the active muscle bundle point to the passive fascia point in the traction matching point pair is used as the actual connection vector of the traction matching point pair; The mean angle between each actual connection vector and the traction direction vector is obtained and used as the traction path deviation angle.

10. The pelvic floor ultrasound key muscle group function quantification system for vaginal laxity according to claim 7, characterized in that, The method of determining the pathological state of vaginal laxity in the examinee based on the ineffective contraction energy coefficient and the deviation angle of the traction path specifically includes: When the ineffective contraction energy coefficient is greater than or equal to the preset energy threshold, the pathological state of vaginal laxity is a ruptured state. When the ineffective contraction energy coefficient is less than the preset energy threshold and the traction path deviation angle is greater than or equal to the preset deviation angle threshold, the pathological state of vaginal laxity is the laxity state. When the ineffective contraction energy coefficient is less than the preset energy threshold and the traction path deviation angle is less than the preset deviation angle threshold, the pathological state of vaginal laxity is normal.

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