Method and equipment for monitoring lower limb vein deformation and blood flow based on M-type ultrasonic technology

Abstract

The invention discloses a method and equipment for monitoring lower limb vein deformation and blood flow based on an M-type ultrasonic technology, and the method comprises the steps: carrying out the M-type ultrasonic scanning of the lower limb skin of a user in a motion state in a preset sampling line direction through a flexible patch type ultrasonic probe; based on a preset grayscale signal gradient condition and a region-of-interest extraction condition, converting the scanned M-type ultrasonic image into a grayscale image, extracting a region-of-interest from the grayscale image, marking a low-pixel line segment representing a blood vessel envelope region in the region-of-interest as a'dark line ', d-type ultrasonic waves of a flexible patch type ultrasonic probe are used for measuring an optimal sampling line of a dark line, integration is carried out on deformation of the dark line along with time, the part between two adjacent waveforms in an obtained broken line graph is marked as a dark area, integration is carried out on changes of the edge and the internal pixel value of the dark area along with time, and the optimal sampling line of the dark line is obtained. And outputting a motion waveform image of the depth positions of the vein tube wall and the vein valve along with the time change, and calculating the vein deformation quantity of the lower limb muscles.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of sports medicine and medical image analysis, and particularly relates to a method and device for monitoring deformation of lower limbs and blood flow based on M-mode ultrasound technology. BACKGROUND

[0002] Deep venous thrombosis (DVT) is a common venous reflux disorder in clinical practice. Acute pulmonary embolism (PE) caused by thrombus detachment is the main adverse consequence of DVT, which can significantly affect the quality of life of patients and even lead to death. According to authoritative journals, the incidence of DVT in ICU is 9.75-31.00%, and if the bedridden time is more than 10 days, the incidence rate is as high as 60%. Like DVT, varicose veins belong to chronic venous disease (CVD), which is a syndrome characterized by a series of symptoms and signs caused by abnormal structure or function of veins, leading to poor venous blood return and high venous pressure. According to relevant statistics, the prevalence of the disease is 8.89%, and the annual incidence is 0.5%-3.0%. The patient population is large, and the incidence and severity gradually increase with age. As can be seen, the prevalence of deep venous thrombosis and varicose veins is high, so early warning is important and helps to reduce the mortality and disability rate of hospitalized patients.

[0003] The pumping function of lower limb muscles is an important link to ensure the return of venous blood to the heart. The existing lower limb venous scanning method is limited by the design characteristics of the traditional ultrasound probe, and lacks effective means for early warning of deep venous thrombosis and varicose veins under the condition of lower limb muscle movement. For example, the current diagnosis of CVD mainly relies on bedside ultrasound instruments for remedial screening of formed thrombus, mainly judging whether thrombus is formed by the compressibility of the venous lumen after the probe is pressed. However, affected by factors such as patient position, imaging quality of bedside ultrasound diagnosis instrument, and timeliness of bedside ultrasound monitoring, the prediction effect of the early stage of DVT formation is poor, and the changes in blood flow dynamics in the venous lumen (such as effective venous lumen diameter, intraluminal blood flow velocity, and venous flow) before thrombosis cannot be timely and effectively monitored, which is the main difficulty in evaluating the risk of venous thrombosis in high-risk patients. At the same time, the lower limbs of most patients are not in an absolute static state during bed rest, so the relative fixation of the flexible probe section also faces challenges. SUMMARY

[0004] In view of the problems in the prior art, the present application provides a method and device for monitoring deformation and blood flow of lower limb veins based on M-mode ultrasound technology, which can monitor the relationship between the deformation of lower limb veins and the change of blood flow under the human motion state according to the change of the preferred M-mode ultrasound image, thereby helping to realize the quantification of lower limb muscle pump function and the prediction of thrombosis risk.

[0005] To solve the above technical problems, the present application realizes the technical scheme as follows: A method for monitoring deformation and blood flow of lower limb veins based on M-mode ultrasound technology, comprising the following steps: Step 1) presetting a gray signal gradient condition and an interested region extraction condition; Step 2) using a flexible patch type ultrasonic probe with a preset frequency to perform M-mode ultrasonic scanning on the skin surface of the lower limb of a user under a motion state in a plurality of preset sampling line directions, to obtain at least one M-mode ultrasound image, wherein the M-mode ultrasound image contains the position of the dynamic and static vein vessel wall of the lower limb of the user and the internal structure information thereof; Step 3) converting the M-mode ultrasound image into a corresponding gray image based on the gray signal gradient condition, and extracting an interested region in the gray image based on the interested region extraction condition; Step 4) based on the gray signal gradient condition, first marking a low-pixel line segment representing a blood vessel envelope region in the interested region as a "dark line", and obtaining the corresponding venous blood flow velocity of the "dark line" by using D-mode ultrasound waves, then selecting the "dark line" with the longest length according to the obtained venous blood flow velocity, and performing displacement-time integration on both ends of the "dark line" to obtain a broken line graph of the "dark line" deformation over time in the most suitable sampling line direction; then marking the part between the adjacent two waveforms in the broken line graph as a "dark area", and performing displacement-time integration on the three pixel points with the highest pixel values in the range of the "dark area" to obtain a curve graph of the edge and internal pixel values of the "dark area" changing over time; finally, manually / automatically tracing the broken line graph and the curve graph to output a motion waveform image of the venous vessel wall and the depth position of the venous valve changing over time, and calculating the volume change amount of the lower limb muscle vein in the short axis direction based on the motion waveform image.

[0006] Step 5) measuring the depth and deformation information of the extracted interested region to obtain analysis parameters including muscle vein area change rate, venous valve mobility, valve opening time and speed, and vortex area self-luminous.

[0007] Further, in step 1, the gray signal gradient condition comprises a first preset pixel value, a second preset length value, a third preset wave amplitude value, a fourth preset wave amplitude value and a fifth preset pixel value. The first preset pixel value is calculated by a quality control personnel using a hand-held / attached calibration probe of a preset reference echo signal to sample the B-mode ultrasound image pixel values of the user's lower limb blood vessels and surrounding tissue region in a standard cross-sectional scanning manner of the target blood vessels. The expression for calculating the first preset pixel value is as follows: F = 0.299*R + 0.587*G + 0.114*B; In the above formula, F is the first preset pixel value, R is the pixel value of the red channel in the B-mode ultrasound image, G is the pixel value of the green channel in the B-mode ultrasound image, and B is the pixel value of the blue channel in the B-mode ultrasound image. The second preset length value, the third preset amplitude value, the fourth preset amplitude value, and the fifth preset pixel value are determined by manual setting and fine-tuned according to different users. The initial assignment of the second preset length value is 5mm. The initial assignment of the third preset amplitude value is 2mm. The initial assignment of the fourth preset amplitude value is 1mm. The initial assignment of the fifth preset pixel value is 5-10.

[0008] Further, in step 1, the region of interest extraction conditions include: a region of interest preset extraction range, a region of interest preset feature, and a region of interest preset depth. The region of interest preset extraction range is a plurality of target regions located within a rectangular region frame of a preset size in the grayscale image; wherein, The width of the rectangular region frame is 20mm above the shallowest blood vessel boundary to 20mm below the deepest blood vessel boundary in the grayscale image, and the length of the rectangular region frame is consistent with the length of the grayscale image, which is 40-100mm. The target region includes: a region from the image upper boundary to the blood vessel upper boundary in the grayscale image, a region from the blood vessel upper boundary to the blood vessel lower boundary in the grayscale image, and a region from the blood vessel lower boundary to the image lower boundary in the grayscale image. The region of interest preset feature includes: a blood vessel region with a blood vessel envelope region width greater than 5mm, and muscle regions with an envelope width of 20mm in the deep and shallow regions based on the upper and lower boundaries of the blood vessel region; The region of interest preset depth is a distance of 5-10cm in the preset sampling line direction.

[0009] Further, in step 2, the preset frequency of the flexible patch-type ultrasound probe is: The linear array probe frequency is 4-12MHz, which is used for monitoring deep veins. Linear array probe frequency 1-6MHz, used to monitor intermuscular veins.

[0010] Further, in step 2, the depth of the M-mode ultrasound image is 40-100mm, the width is 35-45mm, and the time length is 8000-1600ms.

[0011] Further, in step 3, the specific method for extracting the region of interest is: Step 3.1) Based on the preset extraction range of the region of interest, remove the image area outside the upper and lower image boundaries in the grayscale image, and only keep the rectangular area frame with a length consistent with the grayscale image length of 40-100mm and a width of 20mm above the shallowest blood vessel boundary to 20mm below the deepest blood vessel boundary in the grayscale image; Step 3.2) Based on the preset extraction range of the region of interest, determine the image upper boundary to the blood vessel upper boundary area, the blood vessel upper boundary to the blood vessel lower boundary area, and the blood vessel lower boundary to the image lower boundary area within the rectangular area frame; The image upper boundary of the grayscale image is a continuous region where the center point pixel value of a certain row in the grayscale image is less than the fifth preset pixel value to the center point pixel value of the next row in the grayscale image is greater than the fifth preset pixel value; the image lower boundary of the grayscale image is a continuous region where the center point pixel value of a certain row in the grayscale image is greater than the fifth preset pixel value to the center point pixel value of the next row in the grayscale image is less than the fifth preset pixel value; The blood vessel upper boundary of the grayscale image is a boundary where the center point pixel value of a certain row in the grayscale image is greater than the first preset pixel value to the center point pixel value of the next row in the grayscale image is less than the first preset pixel value; the blood vessel lower boundary of the grayscale image is a boundary where the center point pixel value of a certain row in the grayscale image is less than the first preset pixel value to the center point pixel value of the next row in the grayscale image is greater than the first preset pixel value; Step 3.3) Based on the preset features of the region of interest, extract the region of interest including blood vessel regions with a blood vessel envelope region width greater than 5mm and muscle regions with a width of 20mm enveloped from the upper and lower boundaries of the blood vessel region in the three types of regions of the image upper boundary to the blood vessel upper boundary area, the blood vessel upper boundary to the blood vessel lower boundary area, and the blood vessel lower boundary to the image lower boundary area, and the depth of the region of interest is a distance of 5-10cm in the preset sampling line direction, and the one-dimensional image conversion range of the preset sampling line is determined according to the extracted region of interest.

[0012] Further, in step 4, the specific method for obtaining the motion waveform image of the blood vessel wall and valve position changes over time is: Step 4.1) Determine whether the pixel values ​​of all pixels within any length pixel strip in the region of interest are less than the first preset pixel value; if at least two pixels in the region of interest meet the requirement that the pixel value is less than the first preset pixel value, calculate the actual distance between the two farthest adjacent pixels that meet the requirement to obtain the tissue depth range of the region of interest, and determine whether the distance is greater than the second preset length value; if the distance is greater than the second preset length value, define the low pixel value region between the two farthest adjacent pixels that meet the requirement as the venous envelope region, and record it as a "dark line", representing a low pixel line segment with a pixel value lower than the first preset pixel value; Step 4.2) Following the above-described "dark line" identification method, obtain all the "dark lines" in the preset sampling line directions, locate the midpoint of the "dark line", switch to the D-mode ultrasound of the flexible patch ultrasound probe at this position, and set the sampling volume to 1 / 3 of the width of the "dark line" to obtain the blood flow velocity corresponding to all the "dark lines". Label the "dark lines" with a blood flow peak velocity greater than 20 cm / s as arterial source signals, and label the "dark lines" with a blood flow peak velocity less than or equal to 20 cm / s as non-arterial source signals. Filter the echo signals in all the preset sampling line directions, and select the preset sampling line corresponding to the non-arterial source signal with the longest "dark line" length as the optimal sampling line. The direction of this optimal sampling line is then used as the scanning direction for lower limb venous deformation monitoring. Step 4.3) After determining the optimal sampling line, record the initial length of the "dark line" in the direction of the optimal sampling line, and at the same time record the initial minimum pixel value and the initial maximum pixel value of all pixels in the "dark line" area, so as to perform image quality control and early warning on the obtained M-mode ultrasound image. Step 4.4) After determining the optimal sampling line, locate the midpoint of the "dark line" along the optimal sampling line direction, and switch to the D-mode ultrasound mode of the flexible patch ultrasound probe at this position. Set the sampling volume to 1 / 3 of the width of the "dark line" corresponding to the optimal sampling line to obtain the initial blood flow velocity corresponding to the optimal sampling line, so as to perform quality control and early warning on the obtained M-mode ultrasound image. Step 4.5) After determining the optimal sampling line, perform displacement-time integration on the nearest and farthest pixel edges of the "dark line" in the direction of the optimal sampling line to obtain a polygonal graph of the deformation of the regions at both ends of the "dark line" in the direction of the optimal sampling line over time, corresponding to the dynamic waveform of the venous lumen. Step 4.6) record the part between the adjacent two waveforms in the obtained line graph as a "dark area", screen whether there is a pixel point with a pixel value higher than the first pre-degree pixel value in the "dark area", if there is, then according to the spot detection algorithm, carry out displacement-time integration on the three pixel points with the highest pixel values in the "dark area" range meeting the condition, obtain the waveform graph of the "dark area" edge and internal pixel value change with time, and the corresponding venous valve dynamic waveform; Step 4.7) manually / automatically tracing the obtained dynamic waveform of the vessel lumen and the dynamic waveform of the venous valve, finally outputting the user's lower limb venous deformation monitoring scanning direction venous wall and venous valve depth position motion waveform image change with time, and calculating the volume change amount of the lower limb muscle vein in the short axis direction.

[0013] Further, it further includes step 5) measuring the depth and deformation information of the extracted region of interest to obtain analysis parameters including muscle vein area change rate, venous valve dynamic, valve opening time and speed, and eddy current area self-luminous.

[0014] A device for monitoring lower limb venous deformation and blood flow based on M-mode ultrasound technology, comprising: A handheld / attached calibration probe is responsible for standard cross-sectional scanning of the target blood vessels of the user's lower limbs to obtain B-mode ultrasound images of the user's lower limb blood vessels and surrounding tissue regions, which are used for presetting gray signal gradient conditions and region of interest extraction conditions; A preset module is responsible for presetting gray signal gradient conditions and region of interest extraction conditions; A flexible patch-type ultrasound probe is responsible for M-mode ultrasound scanning of the user's lower limb skin surface in multiple preset sampling line directions under the user's motion state, obtaining at least one M-mode ultrasound image containing the user's lower limb arteriovenous wall position and its internal structure information, which is used for one-dimensional image conversion in the later stage; and is responsible for D-mode ultrasound sampling of the midpoint position of the "dark line" determined in the preset sampling line direction, which is used to obtain the blood flow velocity corresponding to the "dark line"; A gray module is responsible for converting the M-mode ultrasound image into a corresponding gray image based on the preset gray signal gradient condition, which is used for region of interest extraction; An extraction module is responsible for extracting the region of interest in the corresponding gray image of the M-mode ultrasound image based on the preset region of interest extraction condition; The definition module is responsible for determining whether the pixel values ​​of all pixels within any length pixel strip in the region of interest are less than a first preset pixel value under the grayscale signal gradient condition. If at least two pixels in the region of interest meet the requirement that their pixel values ​​are less than the first preset pixel value, the module calculates the actual distance between the two farthest adjacent pixels that meet the requirement to obtain the tissue depth range of the region of interest, and determines whether this distance is greater than a second preset length value under the grayscale signal gradient condition. If this distance is greater than the second preset length value, the low pixel value region between the two farthest adjacent pixels that meet the requirement is defined as a venous envelope region and recorded as a "dark line," representing a low pixel line segment with a pixel value lower than the first preset pixel value. Simultaneously, after obtaining all the "dark lines" in the preset sampling line directions, the module uses the blood flow velocity measured by the D-mode ultrasound of the flexible patch-type ultrasound probe to select the preset sampling line corresponding to the longest non-arterial source signal of the "dark line" as the optimal sampling line, and the direction of this optimal sampling line is used as the scanning direction for lower limb venous deformation monitoring. The integration module is responsible for performing displacement-time integration on the nearest and farthest pixel edges of the "dark line" along the optimal sampling line direction after determining the optimal sampling line, to obtain a line graph showing the deformation of the region at both ends of the "dark line" along the optimal sampling line direction over time, corresponding to the motion waveform of the vein lumen; then, the part between two adjacent waveforms in the line graph is recorded as a "dark area", and all pixels in the "dark area" are screened to see if there are any pixels with pixel values ​​higher than the first pre-defined pixel value. If so, displacement-time integration is performed on the three pixels with the highest pixel values ​​within the "dark area" that meet the condition, according to the speckle detection algorithm, to obtain a curve graph showing the change of pixel values ​​at the edge and inside of the "dark area" over time, corresponding to the motion waveform of the venous valve; finally, the module outputs a motion waveform image of the depth position of the vein wall and venous valves over time in the scanning direction of the user's lower limb vein deformation monitoring. The recording module provides an operation platform and display interface for manually recording the dynamic waveforms of the obtained venous lumen and the venous valves, and outputs the motion waveform images of the depth position of the venous wall and venous valves in the scanning direction of the user's lower limb venous deformation monitoring over time. The quality control early warning module is responsible for recording the initial length of the "dark line", the initial minimum pixel value and the initial maximum pixel value of all pixel points in the "dark line" area, and the initial blood flow velocity corresponding to the optimal sampling line in the direction of the optimal sampling line, so as to perform image quality control and early warning on the obtained M-mode ultrasound image; and is responsible for monitoring the motion waveform image of the output venous wall and the depth position of the venous valve changing with time, and if the amplitude of the motion waveform of the venous lumen is less than the third preset amplitude value of the gray signal gradient condition, the amplitude of the motion waveform of the venous valve is less than the fourth preset amplitude value of the gray signal gradient condition, or the pixel value of more than three pixel points in the selected "dark area" is greater than the first preset pixel value of the gray signal gradient condition, the early warning indicator light is turned on and the motion waveform image of the venous wall and the depth position of the venous valve changing with time is uploaded to the local; The analysis module is responsible for calculating the volume change of the lower limb muscle vein in the short axis direction by using the obtained motion waveform image of the venous wall and the depth position of the venous valve changing with time in the scanning direction of the user's lower limb vein deformation monitoring; and is responsible for measuring the depth and deformation information of the extracted "region of interest" to obtain analysis parameters including muscle vein area change rate, venous valve mobility, valve opening time and speed, and vortex area self-development.

[0015] A computer device, comprising: a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete the communication among each other through the communication bus, the memory is used to store at least one executable instruction, and the executable instruction makes the processor execute the operation corresponding to the above-mentioned method for monitoring the deformation and blood flow of lower limb veins based on M-mode ultrasound technology.

[0016] A computer storage medium, at least one executable instruction is stored in the computer storage medium, and the executable instruction makes the processor execute the operation corresponding to the above-mentioned method for monitoring the deformation and blood flow of lower limb veins based on M-mode ultrasound technology.

[0017] The present application relies on the current relatively advanced flexible ultrasound technology, fully utilizes the advantages of small size and real-time monitoring of the technology, selects different attached body surface points according to different positions of the venous lesions, and creatively utilizes the M-mode ultrasound imaging characteristics to perform image algorithm processing on the obtained M-mode ultrasound image without relying on the absolute accuracy of the probe section, uses the motion waveform of the structure inside and outside the venous lumen to evaluate the hemodynamic changes in real time, and predicts the potential risk parameters and the cut-off value of deep venous thrombosis.

[0018] The method of the present application does not rely on the conventional ultrasonic probe section adjustment process, and through M-type ultrasonic scanning of the intraluminal structure and peripheral tissue of the lower limb vein, the optimal scanning section in the vein is positioned through multi-angle M-type ultrasonic scanning lines, and the motion waveform generated by the change of the tissue structure with time in the extracted region of interest is identified, so that the deformation of the intraluminal valve and the vein wall and the distribution of the low-speed blood flow can be detected in real time and quickly, thereby helping to realize the early warning of the lower limb vein thrombosis and low-speed blood flow, and solving the problem that the simple Doppler mode scanning is not sensitive to the lower limb vein thrombosis and low-speed blood flow and consumes a lot of energy.

[0019] The device of the present application can determine the intravenous blood flow dynamics change condition according to the real-time pixel displacement of the muscle tissue, the vein wall and the motility waveform of the intravenous structure, does not need an operator to calibrate the section, monitors the change of the limb vein deformation and blood flow under the human motion state based on the change of the preferred M-type ultrasonic image, so as to achieve the design of quantifying the lower limb muscle pump function or predicting the risk before thrombosis, and therefore the device of the present application can be applied to the conventional vein ultrasonic examination of almost all standing chronic venous disease patients, and helps to achieve the effect of precise treatment.

[0020] Compared with the prior art, the present application has the following advantages: The flexible patch type ultrasonic probe of the present application has good adhesion, can measure the hemodynamic parameters and pressure changes in the intraluminal vein of the patient in the motion / rest state in real time, solves the problem that the traditional ultrasonic probe or single flexible ultrasonic probe is easily disturbed by the lower limb motion muscle and cannot effectively fix the scanning section, and helps to realize the whole period early warning of the lower limb vein thrombosis.

[0021] The flexible patch type ultrasonic probe of the present application adopts a linear array arrangement form, can greatly reduce the scanning time, and all scanning planes can complete the measurement of intravenous related parameters in one motion cycle, solving the problem that the traditional scanning method can only repeatedly scan the patient's vein system in multiple anatomical planes and cannot scan multiple planes at a time.

[0022] The flexible patch type ultrasonic probe of the present application can adopt a patch fixation form, has good measurement consistency and repeatability, and due to the design characteristics of zero pressure and patch pressure monitoring, the pressure of the flexible patch type ultrasonic probe on the body surface is generally constant and controllable, the inter-group difference of different anatomical planes and multiple measurements is small, and the problem that the traditional scanning method cannot overcome the repeatability error caused by multiple calf compression tests is solved.

[0023] The device of the present application has low technical requirements for operators, and the scanning process is not dependent on hand feeling, but on tissue deformation monitoring data, standardized measurement technology indicators, intelligent operation interface, and solves the problem that the traditional ultrasound-guided intervention technology needs to be completed by one hand of the operator holding the probe, and the operator cannot operate the intervention surgical instrument with both hands.

[0024] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, and to implement the content of the specification, the following will be described in detail with the preferred embodiments of the present application and the accompanying drawings. The specific embodiments of the present application are given in detail by the following embodiments and the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0025] The accompanying drawings described herein are used to provide further understanding of the present application, and form a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings: Figure 1 The step flow chart of the method for monitoring the deformation and blood flow of lower limb veins based on M-mode ultrasound technology of the present application; Figure 2 The B-mode ultrasound image of lower limb arteries and veins obtained by the handheld / attached calibration probe of the present application; Figure 3 The M-mode ultrasound image of superficial and deep veins obtained by the flexible patch type ultrasound probe of the present application; Figure 4 The broken line graph of the time-dependent deformation of the regions at both ends of the "dark line" in the most suitable sampling line direction output by the integral module of the present application, and the part between the adjacent two waveforms in the graph is the "dark region"; Figure 5 The motion waveform image of the time-dependent change of the depth position of the vein wall and the vein valve in the scanning direction of the lower limb vein deformation monitoring of the present application output by the tracing module; Figure 6 The structural block diagram of the device for monitoring the deformation and blood flow of lower limb veins based on M-mode ultrasound technology of the present application; Figure 7 The physical diagram of the handheld / attached calibration probe of the present application and the real scene diagram when it is attached to the lower limb of the human body; Figure 8 The fixing schematic diagram of the flexible patch type ultrasound probe of the present application and the lower limb of the user, wherein the left drawing is the calf triceps patching mode, and the right drawing is the popliteal fossa bandage mode; Figure 9 The depth-pixel value broken line graph on the most suitable sampling line (i.e. "dark line") output by the analysis module of the present application. DETAILED DESCRIPTION

[0026] The preferred embodiments of the present application will be described in detail below with reference to the drawings, so as to make the purpose, features and advantages of the present application more clear. It should be understood that the embodiments shown in the drawings are not a limitation on the scope of the present application, but only to illustrate the essential spirit of the technical solutions of the present application.

[0027] In the following description, for the purpose of explaining various disclosed embodiments, certain specific details are set forth in order to provide a thorough understanding of various disclosed embodiments. However, one skilled in the relevant arts will recognize that embodiments can be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures, devices, and techniques associated with the present application are not shown or described in order to avoid unnecessarily obscuring the description of the embodiments.

[0028] In addition, the technical features involved in the different embodiments of the application described below can be combined with each other as long as there is no conflict between them.

[0029] Referring to Figure 1 As shown in the drawings, a method for monitoring deformation and blood flow of lower extremity veins based on M-mode ultrasound technology comprises the following steps: Step 1) presetting gray signal gradient conditions and region of interest extraction conditions.

[0030] The gray signal gradient conditions include a first preset pixel value, a second preset length value, a third preset amplitude value, a fourth preset amplitude value, and a fifth preset pixel value.

[0031] The first preset pixel value is used for the judgment and definition of the late "dark line" and for determining the upper and lower boundaries of the blood vessels in the late gray scale image, and its value is calculated by sampling the pixel value of the B-mode ultrasound image (such as Figure 2 As shown in the drawings) of the user's lower extremity blood vessels (cavity) and surrounding tissue region using a standard cross-sectional scanning method of the target blood vessels with a hand-held / attached calibration probe of the preset reference echo signal, and thus the first preset pixel value of the user is determined.

[0032] The expression for calculating the first preset pixel value is as follows: F = 0.299*R + 0.587*G + 0.114*B; In the above formula, F is the first preset pixel value, R is the pixel value of the red channel in the B-mode ultrasound image, G is the pixel value of the green channel in the B-mode ultrasound image, and B is the pixel value of the blue channel in the B-mode ultrasound image.

[0033] The second preset length value is used for the judgment and definition of the late "dark line", and its value is 5mm, which is determined by manual setting and can be adjusted according to different users.

[0034] The third preset wave amplitude value is used for early warning of the amplitude of the venous lumen in the later stage, and is assigned a value of 2 mm, which is determined by manual setting and can be adjusted according to different users.

[0035] The fourth preset wave amplitude value is used for early warning of the amplitude of the venous valve in the later stage, and is assigned a value of 1 mm, which is determined by manual setting and can be adjusted according to different users.

[0036] The fifth preset pixel value is used to determine the upper and lower boundaries of the image of the grayscale image, and is assigned a value of 5-10, which is determined by manual setting and can be adjusted according to different users.

[0037] The region of interest extraction condition includes a region of interest preset extraction range, a region of interest preset feature, and a region of interest preset depth.

[0038] The region of interest preset extraction range is a plurality of target regions located in a rectangular region frame of a preset size in the grayscale image. The size of the grayscale image display area determines the preset size of the rectangular region, the width of the rectangular region frame is 20 mm above the shallowest blood vessel boundary to 20 mm below the deepest blood vessel boundary in the grayscale image, and the length of the rectangular region frame is consistent with the length of the grayscale image, which is 40-100 mm (the size of the rectangular region frame is set according to the shallowest blood vessel boundary and the deepest blood vessel boundary in the B-mode ultrasound image scanned by the handheld / attached calibration probe). The target region includes: a region from the image upper boundary to the blood vessel upper boundary in the grayscale image, a region from the blood vessel upper boundary to the blood vessel lower boundary in the grayscale image, and a region from the blood vessel lower boundary to the image lower boundary in the grayscale image.

[0039] The image upper boundary of the grayscale image is a continuous region in which the pixel value of a center point of a certain row in the grayscale image is less than the fifth preset pixel value and the pixel value of a center point of the next row in the grayscale image is greater than the fifth preset pixel value.

[0040] The image lower boundary of the grayscale image is a continuous region in which the pixel value of a center point of a certain row in the grayscale image is greater than the fifth preset pixel value and the pixel value of a center point of the next row in the grayscale image is less than the fifth preset pixel value.

[0041] The blood vessel upper boundary of the grayscale image is a boundary in which the pixel value of a center point of a certain row in the grayscale image is greater than the first preset pixel value and the pixel value of a center point of the next row in the grayscale image is less than the first preset pixel value.

[0042] The lower blood vessel boundary of the gray scale image is a boundary in which a center point pixel value of a certain row in the gray scale image is less than the first preset pixel value to a center point pixel value of a next row in the gray scale image is greater than the first preset pixel value.

[0043] The preset feature of the region of interest includes a blood vessel region in which a width of a blood vessel envelope region is greater than 5 mm, and a muscle region in which a width of an envelope region is 20 mm, and which is enveloped to a deep region and a shallow region with respect to upper and lower boundaries of the blood vessel region as a reference.

[0044] The preset depth of the region of interest is a distance of 5-10 cm in the preset sampling line direction.

[0045] Step 2) M-mode ultrasonic scanning is performed on a skin surface of a lower limb of a user in a motion state in at least three preset sampling line directions by using a flexible patch ultrasonic probe with a preset frequency, and at least one M-mode ultrasonic image (as shown in Figure 3 The depth of the M-mode ultrasonic image is 40-100 mm, the width is 35-45 mm, and the time length is 8000-1600 ms. The M-mode ultrasonic image contains a position of a vein wall of a lower limb of the user and internal structure information thereof.

[0046] The frequency of the flexible patch ultrasonic probe is 4-12 Mhz, and is used for monitoring deep veins.

[0047] The frequency of the flexible patch ultrasonic probe is 1-6 Mhz, and is used for monitoring intermuscular veins.

[0048] Step 3) The M-mode ultrasonic image is converted into a corresponding gray scale image based on the gray scale signal gradient condition, and a region of interest is extracted in the gray scale image based on the region of interest extraction condition. The specific method is as follows: Step 3.0) The M-mode ultrasonic image is converted into a gray scale image in which upper and lower boundaries of the image and upper and lower boundaries of blood vessels are determined based on the first preset gray scale value and the fifth preset gray scale value. Step 3.1) Based on the preset extraction range of the region of interest, image regions other than the upper and lower boundaries of the image in the gray scale image are removed, and only a rectangular region frame with a length consistent with the length of the gray scale image (40-100 mm) and a width of 20 mm above the shallowest blood vessel boundary to 20 mm below the deepest blood vessel boundary in the gray scale image is reserved.

[0049] Step 3.2) Based on the preset extraction range of the region of interest, the region of interest is determined in the rectangular region frame from the upper boundary of the image to the upper boundary of the blood vessel, from the upper boundary of the blood vessel to the lower boundary of the blood vessel, and from the lower boundary of the blood vessel to the lower boundary of the image.

[0050] Step 3.3) Based on the preset features of the region of interest, extract the region of interest including the blood vessel region with a width of the blood vessel envelope region greater than 5 mm and the muscle region with a width of 20 mm enveloped from the upper and lower boundaries of the blood vessel region, and the depth of the region of interest is 5-10 cm in the preset sampling line direction, and determine the one-dimensional image conversion range of the preset sampling line according to the extracted region of interest.

[0051] Step 4) Based on the gray signal gradient condition, first mark the low pixel line segment representing the blood vessel envelope region in the region of interest as "dark line", and obtain the venous blood flow velocity corresponding to the "dark line" using D-type ultrasonic waves, then select the "dark line" with the longest length according to the obtained venous blood flow velocity, and perform displacement-time integration on both ends to obtain the broken line graph of the "dark line" deformation over time in the most suitable sampling line direction; then mark the part between the adjacent two waveforms in the broken line graph as "dark area", and perform displacement-time integration on the three pixel points with the highest pixel values in the range to obtain the curve graph of the edge and internal pixel values of the "dark area" changing over time; finally, manually / automatically trace the broken line graph and the curve graph, output the motion waveform image of the depth position of the venous wall and the venous valve changing over time, and calculate the volume change amount of the lower limb muscle vein in the short axis direction; the specific method is as follows: Step 4.1) Determine whether the pixel values (at least two pixel values) of all pixel points in the arbitrary length pixel strip in the region of interest are less than the first preset pixel value; if there are at least two pixel points in the region of interest that satisfy the requirement that the pixel value is less than the first preset pixel value, calculate the actual distance between the two most adjacent pixel points that satisfy the requirement to obtain the tissue depth range of the region of interest, and determine whether the distance is greater than the second preset length value; if the distance is greater than the second preset length value, define the low pixel value region between the two most adjacent pixel points that satisfy the requirement as a venous envelope region, and mark it as a "dark line" representing a low pixel line segment with a pixel value less than the first preset pixel value; on the contrary, if the distance is less than the second preset length value, define the low pixel value region between the two most adjacent pixel points as a muscle tissue region.

[0052] Step 4.2) Obtain all the "dark lines" of the preset sampling line direction according to the "dark line" identification method described above, locate the position of the midpoint of the "dark line", switch to the D-mode ultrasound mode of the flexible patch-type ultrasound probe at this position, and set the sampling volume to 1 / 3 of the width of the "dark line", so as to obtain the blood flow velocity corresponding to all the "dark lines"; mark the "dark line" with a blood flow peak velocity greater than 20 cm / s as an arterial source signal, and mark the "dark line" with a blood flow peak velocity less than or equal to 20 cm / s as a non-arterial source signal, screen all the echo signals in the preset sampling line direction, and select the preset sampling line corresponding to the non-arterial source signal with the longest "dark line" length as the optimal sampling line (which can be one or more), and the direction of the optimal sampling line is the lower limb vein deformation monitoring scanning direction.

[0053] Step 4.3) After determining the optimal sampling line, record the initial length of the "dark line" in the direction of the optimal sampling line, and record the initial minimum pixel value and the initial maximum pixel value of all pixel points in the "dark line" region, so as to perform image quality control and early warning on the obtained M-mode ultrasound image.

[0054] The situations that need to be prompted for quality control during monitoring include: the real-time monitoring length of the "dark line" is less than 50% of the initial length or greater than 150% of the initial length, and the maximum pixel value in the "dark line" is greater than 50% of the initial maximum pixel value.

[0055] The situations that need to be prompted for early warning during monitoring include: the maximum pixel value in the "dark line" is greater than 150% of the initial maximum pixel value, and any region with a length greater than 1 mm and a pixel value higher than the first preset pixel value appears in the "dark line".

[0056] When it is judged that most of the pixel points in the region of interest are not all less than the first preset pixel value, or the first preset pixel value and the second preset length value conditions cannot be met at the same time, so that the "dark line" and the "dark area" cannot be marked, the generated image should be classified as a situation that needs image quality control and early warning.

[0057] Step 4.4) After determining the optimal sampling line, locate the position of the midpoint of the "dark line" in the direction of the optimal sampling line, switch to the D-mode ultrasound mode of the flexible patch-type ultrasound probe at this position, and set the sampling volume to 1 / 3 of the width of the "dark line" corresponding to the optimal sampling line, so as to obtain the initial blood flow velocity corresponding to the optimal sampling line.

[0058] If the situation that needs image quality control and early warning in step 4.3 occurs, the intracavity blood flow velocity spectrum at that time can be obtained, and the situation that needs early warning is that the real-time blood flow peak velocity is less than 5 cm / s.

[0059] Step 4.5) After determining the optimal sampling line, the displacement-time integral of the nearest and farthest pixel edges of the "dark line" in the direction of the optimal sampling line is performed (i.e. the displacement-time integral of the pixel segment length deformation of the "dark line" in the direction of the optimal sampling line), and a polyline graph of the time deformation of the "dark line" at both ends in the direction of the optimal sampling line is obtained (as shown in Figure 4 ).The polyline graph is a wave-like non-periodic waveform, corresponding to the compliance waveform of the vein lumen.

[0060] Step 4.6) The part between the adjacent two waveforms in the obtained polyline graph is recorded as a "dark area", and it is screened whether there are pixel points with pixel values higher than the first pre-degree pixel value in all the "dark areas". If there are, the displacement-time integral line of the three pixel points with the highest pixel values in the "dark area" range that meet the condition is obtained according to the spot detection algorithm, and a waveform graph of the time variation of the pixel values of the "dark area" edge and interior is obtained, corresponding to the compliance waveform of the vein valve (or other intraluminal objects).

[0061] Step 4.7) After obtaining the compliance waveforms of the vein lumen and the vein valve (or other intraluminal objects), they are respectively artificially / automatically traced, and a motion waveform image of the time variation of the vein wall and the depth position of the vein valve in the scanning direction of the user's lower limb vein deformation monitoring is output (as shown in Figure 5 ), and the volume variation of the lower limb muscle vein in the short axis direction is calculated.

[0062] Figure 5 In the above formula, the abscissa represents time, and the ordinate represents the depth coordinate value. Figure 5 In the above formula, A1, B1, B2 and A2 are four curves, which are four tracing curves appearing in the order of depth on the image with the upper boundary (skin surface) as the depth coordinate axis reference (i.e. Figure 4 ). Figure 4 The curve of B1 is the mirror image of the curve of A1, the curve of B2 is the mirror image of the curve of A2, and the curve of A1 is the mirror image of the curve of B1. Figure 5

[0063] The calculation formula of the volume variation of the lower limb muscle vein in the short axis direction is as follows: ; In formula (3), a0 is the average major semi-axis of all elliptical sections, with the unit of centimeter; S i is the motion amplitude in the short axis direction of the i-th acquisition point, i.e. the variation of the minor semi-axis; n is the total number of acquisition points; d is the distance between adjacent acquisition points, with the unit of centimeter.

[0064] The conditions requiring prompt prewarning in the monitoring process include: the amplitude of the venous lumen motility waveform is less than the third preset amplitude value; the amplitude of the venous valve (or other intraluminal object) motility waveform is less than the fourth preset amplitude value; three or more pixel points in the selected "dark area" are greater than the first preset pixel value.

[0065] Step 5) depth and deformation information of the extracted region of interest is measured to obtain analysis parameters including muscle vein area change rate, venous valve motility, valve opening time and speed, and vortex area autography, so that the deformation of the muscle vein and the popliteal vein and the femoral vein with the calf muscle movement and the venous valve motility can be quickly evaluated, and the venous blood flow change value can be determined according to the real-time pixel value change of the muscle tissue and the muscle vein and the motility parameters of the popliteal vein and the femoral vein valve, which can be used to evaluate the risk of thrombosis in the lower limb veins and timely prewarning.

[0066] In summary, the method of the present application does not rely on the conventional ultrasonic probe section adjustment process, and the lower limb vein lumen structure and the surrounding tissue are scanned by M-type ultrasound, the optimal scanning section in the vein is positioned by multi-angle M-type ultrasound scanning line, and the motion waveform generated by the change of the tissue structure with time in the extracted region of interest is identified, so that the deformation of the valve and the vein wall in the vein lumen and the low-speed blood flow distribution can be detected in real time and quickly, thereby helping to realize the prewarning of lower limb vein thrombosis and low-speed blood flow, and solving the problem of low sensitivity and high energy consumption of pure Doppler mode scanning for lower limb vein thrombosis and low-speed blood flow.

[0067] The method of the present application can be used for pre-exercise and post-exercise monitoring, and the changes of the lower limb vein deformation and blood flow velocity of the user before and after exercise can be compared, so that a corresponding intervention scheme can be formulated to reduce the risk of the user suffering from chronic venous diseases such as lower limb vein thrombosis and varicose veins, or to intervene in the treatment of the user who has chronic venous diseases such as lower limb vein thrombosis and varicose veins.

[0068] Referring to Figure 6 The present application also provides a device for monitoring lower limb vein deformation and blood flow based on M-type ultrasound technology, which comprises: (1) a handheld / attached calibration probe (as shown in Figure 7 The device is responsible for standard section scanning of the target blood vessels of the lower limbs of the user to obtain B-mode ultrasound images of the blood vessels (intraluminal) and the surrounding tissue regions of the lower limbs of the user, which are used for presetting the gray signal gradient condition and the region of interest extraction condition.

[0069] (2) a preset module, which is responsible for presetting the gray signal gradient condition and the region of interest extraction condition.

[0070] The gray scale signal gradient condition comprises a first preset pixel value, a second preset length value, a third preset wave amplitude value, a fourth preset wave amplitude value and a fifth preset pixel value.

[0071] The first preset pixel value is used for judging and defining the late "dark line" and determining the upper and lower boundaries of the blood vessels in the late gray scale image, and is calculated by sampling the pixel values of the B-mode ultrasound image (such as Figure 2 ) of the user's lower limb blood vessels (cavity) and surrounding tissue region in the standard cross-section scanning mode of the target blood vessels using the preset reference echo signal hand-held / attached calibration probe by the quality control personnel (professional ultrasound practitioners).

[0072] The expression for calculating the first preset pixel value is as follows: F = 0.299*R + 0.587*G + 0.114*B; In the above formula, F is the first preset pixel value, R is the pixel value of the red channel in the B-mode ultrasound image, G is the pixel value of the green channel in the B-mode ultrasound image, and B is the pixel value of the blue channel in the B-mode ultrasound image.

[0073] The second preset length value is used for judging and defining the late "dark line", and its value is 5mm, which is determined by manual setting and can be fine-tuned according to the different users.

[0074] The third preset wave amplitude value is used for early warning of the amplitude of the venous lumen motility waveform, and its value is 2mm, which is determined by manual setting and can be fine-tuned according to the different users.

[0075] The fourth preset wave amplitude value is used for early warning of the amplitude of the venous valve motility waveform, and its value is 1mm, which is determined by manual setting and can be fine-tuned according to the different users.

[0076] The fifth preset pixel value is used for determining the upper and lower boundaries of the image in the late gray scale image, and its value is 5-10, which is determined by manual setting and can be fine-tuned according to the different users.

[0077] The region of interest extraction condition comprises a region of interest preset extraction range, a region of interest preset feature and a region of interest preset depth.

[0078] The region of interest preset extraction range is a plurality of target regions located in a rectangular region frame of a preset size in the gray scale image; wherein, The size of the gray scale image display area determines the preset size of the rectangular area, the width of the rectangular area frame is 20mm above the shallowest blood vessel boundary to 20mm below the deepest blood vessel boundary in the gray scale image, and the length of the rectangular area frame is consistent with the length of the gray scale image, which is 40-100mm (the size of the rectangular area frame is set according to the shallowest blood vessel boundary and the deepest blood vessel boundary in the B-mode ultrasound image scanned by the handheld / attached calibration probe). The target area includes: the area from the image upper boundary to the blood vessel upper boundary in the gray scale image, the area from the blood vessel upper boundary to the blood vessel lower boundary in the gray scale image, and the area from the blood vessel lower boundary to the image lower boundary in the gray scale image.

[0079] The image upper boundary of the gray scale image is a continuous area in which the pixel value of a center point of a certain row in the gray scale image is less than the fifth preset pixel value and the pixel value of a center point of the next row in the gray scale image is greater than the fifth preset pixel value.

[0080] The image lower boundary of the gray scale image is a continuous area in which the pixel value of a center point of a certain row in the gray scale image is greater than the fifth preset pixel value and the pixel value of a center point of the next row in the gray scale image is less than the fifth preset pixel value.

[0081] The blood vessel upper boundary of the gray scale image is a boundary in which the pixel value of a center point of a certain row in the gray scale image is greater than the first preset pixel value and the pixel value of a center point of the next row in the gray scale image is less than the first preset pixel value.

[0082] The blood vessel lower boundary of the gray scale image is a boundary in which the pixel value of a center point of a certain row in the gray scale image is less than the first preset pixel value and the pixel value of a center point of the next row in the gray scale image is greater than the first preset pixel value.

[0083] The preset features of the region of interest include: a blood vessel region with a blood vessel envelope region width greater than 5mm, and a muscle region with an envelope width of 20mm from the upper and lower boundaries of the blood vessel region to the deep and shallow regions respectively; and a one-dimensional image conversion range of the M-type sampling line is determined according to the above envelope region.

[0084] The preset depth of the region of interest is a distance of 5-10cm in the preset sampling line direction.

[0085] (3) A flexible patch type ultrasonic probe is responsible for M-type ultrasonic wave scanning of the skin surface of the lower limbs of the user in a plurality of preset sampling line directions under the motion state of the user, to obtain at least one M-type ultrasonic image containing the position of the arterial and venous vessel walls of the lower limbs of the user and the internal structure information thereof, for one-dimensional image conversion in the later stage; and is responsible for positioning the midpoint position of the “dark line” of the preset sampling line direction, using a D-type ultrasonic mode, and setting the sampling volume to 1 / 3 of the width of the “dark line”, to obtain the blood flow velocity corresponding to all the “dark lines”.

[0086] In combination with clinical practice, the depth of the deep vein is about 2-10 cm from the body surface, and the measurement accuracy is 0.1 mm. The flexible patch type ultrasonic probe is designed as follows: The scanning system includes a line array probe with a preset frequency, and the line array probe is composed of 3-5 groups of patch probes that can work simultaneously. Each group of the patch probes has 2-3 probes working in parallel, and each probe can emit M-mode ultrasonic waves and D-mode ultrasonic waves. The frequency of the line array probe is preset to 4-12 Mhz, which can be used for monitoring deep veins; the frequency of the line array probe is preset to 1-6 Mhz, which can be used for monitoring intermuscular veins. Referring to Figure 8 As shown in the drawings, the line array probe is adjusted and fixed to the corresponding part of the lower limbs of the user through the gastrocnemius muscle patch (left drawing) or the popliteal bandage structure (right drawing).

[0087] The patch type line array probe is designed to detect the intracavity blood flow changes of the intermuscular veins of the user under three environments of rest, muscle contraction and external pressure. The patch probes of the patch type line array probe are fixed to the inner side of the medical patch through the embedded clamping slot, and the scanning effect after fixation can be achieved through a small amount of coupling agent or coupling pad. The outer side of the medical patch is designed with a body surface calibration line.

[0088] The bandage type line array probe is designed to detect the intracavity blood flow changes of the femoral vein, popliteal vein, femoral vein and its branch veins of the user under two environments of rest and walking. The patch probes of the bandage type line array probe are fixed to the inner side of the quick-release bandage through the embedded clamping slot, and the scanning effect after fixation can be achieved through a small amount of coupling agent. The outer side of the quick-release bandage is designed with a body surface calibration line.

[0089] Prompt arrows are designed on the surface of the fixing structure of the patch type line array probe and the bandage type line array probe. When the user uses the patch type line array probe and the bandage type line array probe to scan the lower limb veins, the probe may be displaced due to the movement of the user's lower limbs, resulting in failure to obtain the optimal M-type sampling line. At this time, the scanning position can be adjusted through the prompt arrow to achieve the purpose of adjusting the scanning section.

[0090] (4) A gray scale module is responsible for converting the M-mode ultrasonic image into a gray scale image that determines the upper and lower boundaries of the image and the upper and lower boundaries of the blood vessels based on the first preset gray scale value and the fifth preset gray scale value, and is used for extraction of the region of interest.

[0091] (5) An extraction module is responsible for extracting the region of interest in the corresponding gray scale image of the M-mode ultrasonic image based on the preset extraction conditions of the region of interest.

[0092] First, based on the preset extraction range of the region of interest, remove the image area outside the upper and lower image boundaries in the grayscale image, and only keep the rectangular area frame with a length consistent with the grayscale image length of 40-100 mm and a width of 20 mm above the shallowest blood vessel boundary to 20 mm below the deepest blood vessel boundary in the grayscale image; then, based on the preset extraction range of the region of interest, determine the image upper boundary to the blood vessel upper boundary region, the blood vessel upper boundary to the blood vessel lower boundary region, and the blood vessel lower boundary to the image lower boundary region within the rectangular area frame; finally, based on the preset characteristics of the region of interest, extract the region of interest including the blood vessel region with a blood vessel envelope region width greater than 5 mm and the muscle region within the envelope width of 20 mm from the upper and lower boundaries of the blood vessel region in the three types of regions of the image upper boundary to the blood vessel upper boundary region, the blood vessel upper boundary to the blood vessel lower boundary region, and the blood vessel lower boundary to the image lower boundary region, and the depth of the region of interest is 5-10 cm in the preset sampling line direction. The one-dimensional image conversion range of the preset sampling line is determined according to the extracted region of interest.

[0093] (6) Definition module, responsible for judging whether the pixel value (at least two pixel values) of all pixel points in any length pixel strip in the region of interest is less than the first preset pixel value of the gray signal gradient condition; if at least two pixel points in the region of interest satisfy the requirement that the pixel value is less than the first preset pixel value, calculate the actual distance between the nearest two pixel points that satisfy the requirement to obtain the tissue depth range of the region of interest, and judge whether the distance is greater than the second preset length value of the gray signal gradient condition; if the distance is greater than the second preset length value, define the low pixel value region between the nearest two pixel points that satisfy the requirement as a vein envelope region, and mark it as a "dark line", which represents a low pixel segment with a pixel value lower than the first preset pixel value; on the contrary, if the distance is less than the second preset length value, define the low pixel value region between the nearest two pixel points as a muscle tissue region; at the same time, after obtaining all the "dark lines" in the preset sampling line direction, according to the blood flow velocity measured by the D-mode ultrasonic mode of the flexible patch ultrasonic probe, the "dark line" with a blood flow peak velocity greater than 20 cm / s is marked as an arterial source signal, and the "dark line" with a blood flow peak velocity less than or equal to 20 cm / s is marked as a non-arterial source signal. All echo signals in the preset sampling line direction are screened, and the preset sampling line corresponding to the non-arterial source signal with the longest "dark line" length is selected as the most suitable sampling line (which can be one or more), and the most suitable sampling line direction is used as the lower limb vein deformation monitoring scanning direction.

[0094] (7) integral module, responsible for determining the optimal sampling line, the "dark line" in the direction of the most suitable for the displacement-time integration of the nearest and farthest two end pixel edge (i.e. the displacement-time integration of the pixel line segment length deformation of the "dark line" in the direction of the most suitable for sampling line), get the "dark line" in the direction of the most suitable for sampling line two end area with time deformation polyline, the polyline is wave type non-periodic waveform, corresponding to the dynamic waveform of the vein lumen; Then the part between the adjacent two waveforms in the polyline is recorded as a "dark area", and whether there is a pixel point with a pixel value higher than the first preset pixel value in all the "dark areas" is screened, if yes, according to the spot detection algorithm, the displacement-time integration of the three pixel points with the highest pixel value in the "dark area" range meeting the condition is carried out, and the curve graph of the pixel value of the "dark area" edge and internal with time is obtained, corresponding to the dynamic waveform of the vein valve (or other intraluminal objects).

[0095] (8) tracing module, used for providing operation platform and display interface for manual tracing of the obtained dynamic waveform of the vein lumen and the dynamic waveform of the vein valve, and outputting the motion waveform image of the vein wall and the depth position of the vein valve of the user's lower extremity vein deformation monitoring scanning direction with time after tracing; (9) quality control and early warning module, responsible for recording the initial length of the "dark line" in the direction of the most suitable for sampling line, the initial minimum pixel value and the initial maximum pixel value of all pixel points in the "dark line" area, and the initial blood flow velocity corresponding to the most suitable for sampling line, so as to carry out image quality control and early warning on the obtained M-mode ultrasound image; responsible for monitoring the output motion waveform image of the vein wall and the depth position of the vein valve with time, if the amplitude of the dynamic waveform of the vein lumen is less than the third preset amplitude value of the gray signal gradient condition, the amplitude of the dynamic waveform of the vein valve (or other intraluminal objects) is less than the fourth preset amplitude value of the gray signal gradient condition, or more than three pixel points in the selected "dark area" have a pixel value greater than the first preset pixel value of the gray signal gradient condition, the warning indicator light is on and the motion waveform image of the vein wall and the depth position of the vein valve with time is uploaded to the local.

[0096] In the monitoring process, the situations that need to be prompted for quality control include: the real-time monitoring length of the "dark line" is less than 50% of the initial length or greater than 150% of the initial length, and the maximum pixel value in the "dark line" is greater than 50% of the initial maximum pixel value.

[0097] The following situations require warnings during monitoring: the maximum pixel value within the "dark line" is greater than 150% of the initial maximum pixel value; an area with a length greater than 1 mm and a pixel value higher than the first preset pixel value appears within the "dark line"; the amplitude of the motion waveform of the venous lumen is less than the third preset amplitude value; the amplitude of the motion waveform of the venous valve (or other intraluminal object) is less than the fourth preset amplitude value; or more than three pixels with a value greater than the first preset pixel value appear within the selected "dark area".

[0098] If the above-mentioned situations requiring quality control and early warning are encountered, the intracavitary blood flow velocity spectrum at that moment can be obtained in the same way. The situation requiring early warning is: the real-time blood flow peak velocity is less than 5cm / s.

[0099] When it is determined that most pixels in the region of interest are not all smaller than the first preset pixel value, or the conditions of the first preset pixel value and the second preset length value cannot be met simultaneously, the "dark line" and "dark area" cannot be marked. In this case, the generated image should be classified as a situation requiring image quality control and early warning.

[0100] (10) Analysis module, which is responsible for using the motion waveform image of the depth position of the vein wall and vein valve in the scanning direction of the user's lower limb vein deformation monitoring to calculate the volume change of the lower limb muscle vein in the short axis direction; and is responsible for measuring the depth and deformation information of the extracted region of interest to obtain analysis parameters including the rate of change of muscle vein area, vein valve mobility, valve opening time and speed, and autoradiography of eddy current area, so as to quickly evaluate the deformation of muscle vein, popliteal vein, and femoral vein with the movement of calf muscles and the mobility of vein valve.

[0101] In some preferred embodiments, the analysis module can further determine the change in venous blood flow based on the real-time pixel value changes of muscle tissue and myovenous tissue, as well as the dynamic parameters of the popliteal and femoral vein valves, thereby assessing the risk of lower extremity venous thrombosis and providing timely warnings.

[0102] See Figure 9 As shown, in some preferred embodiments, the analysis module can also output a depth-pixel value line graph of the optimal sampling line direction (i.e., the "dark line"). Figure 9 The horizontal axis represents depth (a total of 147 consecutive pixels from shallow to deep), and the vertical axis represents the depth coordinate value (ranging from approximately 0 to 80). The solid black line represents the first preset pixel value in this embodiment (approximately 14). After obtaining a B-mode ultrasound image using the handheld / attached calibration probe and performing manual calibration, the analysis module samples and analyzes the hypoechoic region within the returned venous cavity to obtain this depth-pixel value line graph, thereby indirectly determining the appropriate size of the first preset pixel value.

[0103] The above device can determine the change of intravenous hemodynamics according to the real-time pixel displacement of muscle tissue, muscle vein wall and the motility waveform of intravenous structure, without the need for an operator to calibrate the section, and monitor the change of the deformation of the limb vein and blood flow under the human motion state based on the change of the preferred M-mode ultrasound image, so as to achieve the design of quantifying the lower limb muscle pump function or predicting the pre-thrombosis risk.

[0104] The application further provides a computer device (such as a personal computer, a server or a network device), which comprises a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete communication with each other through the communication bus, the memory is used for storing at least one executable instruction, and the executable instruction makes the processor execute the operation corresponding to the method for monitoring the deformation of the lower limb vein and blood flow based on the M-mode ultrasound technology.

[0105] The application further provides a computer storage medium (such as a ROM / RAM, a magnetic disc, an optical disc and the like), and at least one executable instruction is stored in the computer storage medium, and the executable instruction makes the processor execute the operation corresponding to the method for monitoring the deformation of the lower limb vein and blood flow based on the M-mode ultrasound technology.

[0106] The above only describes the preferred embodiments of the application and is not used to limit the application. For those skilled in the art, the application can have various changes and modifications. Any modification, equivalent replacement, improvement and the like within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method of monitoring deformation and blood flow in lower extremity veins based on M-mode ultrasound technology, characterized in that, The method comprises the following steps: Step 1) presetting a gray signal gradient condition and an interested region extraction condition; Step 2) using a flexible patch type ultrasonic probe with a preset frequency to perform M-mode ultrasonic scanning on the skin surface of the lower limbs of the user in a plurality of preset sampling line directions, and obtaining at least one M-mode ultrasonic image, wherein the M-mode ultrasonic image contains the positions of the arterial and venous vessel walls of the lower limbs of the user and internal structure information thereof; Step 3) converting the M-mode ultrasonic image into a corresponding gray image based on the gray signal gradient condition, and extracting an interested region in the gray image based on the interested region extraction condition; Step 4) based on the gray signal gradient condition, first marking a low-pixel line segment representing a blood vessel envelope region in the interested region as a "dark line", and obtaining the corresponding venous blood flow velocity of the "dark line" by using D-mode ultrasonic waves, then selecting the "dark line" with the longest length according to the obtained venous blood flow velocity, and performing displacement-time integration on both ends of the "dark line" to obtain a broken line graph of the "dark line" deformation over time in the most suitable sampling line direction; then marking the part between two adjacent waveforms in the broken line graph as a "dark area", and performing displacement-time integration on the three pixel points with the highest pixel values in the range of the "dark area" to obtain a curve graph of the edge and internal pixel values of the "dark area" changing over time; finally, tracing the broken line graph and the curve graph to output a motion waveform image of the venous vessel wall and the depth position of the venous valve changing over time, and calculating the volume change amount of the lower limb muscle vein in the short axis direction based on the motion waveform image.

2. The method for monitoring deformation and blood flow in lower extremity veins based on M-mode ultrasound technology according to claim 1, characterized in that, In step 1, the gray signal gradient condition comprises a first preset pixel value, a second preset length value, a third preset amplitude value, a fourth preset amplitude value and a fifth preset pixel value; The first preset pixel value is calculated by a quality control personnel using a hand-held / attached calibration probe with a preset reference echo signal to sample the pixel values of the B-mode ultrasonic image of the lower limb blood vessels and the surrounding tissue region of the user in a standard cross-sectional scanning manner of the target blood vessel; The expression for calculating the first preset pixel value is as follows: F = 0.299*R + 0.587*G + 0.114*B; In the above formula, F is the first preset pixel value, R is the pixel value of the red channel in the B-mode ultrasonic image, G is the pixel value of the green channel in the B-mode ultrasonic image, and B is the pixel value of the blue channel in the B-mode ultrasonic image; The second preset length value, the third preset amplitude value, the fourth preset amplitude value and the fifth preset pixel value are determined by manual setting and are adaptively fine-tuned according to different users, wherein The initial assignment of the second preset length value is 5 mm; The initial assignment of the third preset amplitude value is 2 mm; The initial assignment of the fourth preset amplitude value is 1 mm; The initial assignment of the fifth preset pixel value is 5-10.

3. The method of monitoring deformation and blood flow in lower extremity veins based on M-mode ultrasound technology according to claim 2, characterized in that, In step 1, the interested region extraction condition comprises an interested region preset extraction range, an interested region preset feature and an interested region preset depth; The interested region preset extraction range is a plurality of target regions located in a rectangular region frame with a preset size in the gray image; wherein, The width of the rectangular region frame is 20 mm above the shallowest blood vessel boundary to 20 mm below the deepest blood vessel boundary in the grayscale image, and the length of the rectangular region frame is consistent with the length of the grayscale image, being 40-100 mm; The target region includes: a region from the image upper boundary to the blood vessel upper boundary in the grayscale image, a region from the blood vessel upper boundary to the blood vessel lower boundary in the grayscale image, and a region from the blood vessel lower boundary to the image lower boundary in the grayscale image; The preset feature of the region of interest includes: a blood vessel region with a blood vessel envelope region width greater than 5 mm, and a muscle region with an envelope width of 20 mm to the deep and shallow regions based on the upper and lower boundaries of the blood vessel region; The preset depth of the region of interest is a distance of 5-10 cm in the preset sampling line direction.

4. The method for monitoring deformation and blood flow in lower extremity veins based on M-mode ultrasound technology according to claim 1, characterized in that, In step 2, the preset frequency of the flexible patch-type ultrasonic probe is 4-12 MHz for monitoring deep veins and 1-6 MHz for monitoring intermuscular veins; the depth of the M-mode ultrasonic image is 40-100 mm, the width is 35-45 mm, and the time length is 8000-1600 ms.

5. The method for monitoring deformation and blood flow in lower extremity veins based on M-mode ultrasound technology according to claim 3, characterized in that, In step 3, the specific method for extracting the region of interest is: Step 3.1) Based on the preset extraction range of the region of interest, remove the image region outside the image upper boundary and the image lower boundary in the grayscale image, and only keep a rectangular region frame with a length consistent with the length of the grayscale image, 40-100 mm, and a width of 20 mm above the shallowest blood vessel boundary to 20 mm below the deepest blood vessel boundary in the grayscale image; Step 3.2) Based on the preset extraction range of the region of interest, determine the image upper boundary to the blood vessel upper boundary region, the blood vessel upper boundary to the blood vessel lower boundary region, and the blood vessel lower boundary to the image lower boundary region in the rectangular region frame; The image upper boundary of the grayscale image is a continuous region in which the pixel value of the center point of a certain row in the grayscale image is less than the fifth preset pixel value and the pixel value of the center point of the next row in the grayscale image is greater than the fifth preset pixel value; the image lower boundary of the grayscale image is a continuous region in which the pixel value of the center point of a certain row in the grayscale image is greater than the fifth preset pixel value and the pixel value of the center point of the next row in the grayscale image is less than the fifth preset pixel value; The blood vessel upper boundary of the grayscale image is a boundary in which the pixel value of the center point of a certain row in the grayscale image is greater than the first preset pixel value and the pixel value of the center point of the next row in the grayscale image is less than the first preset pixel value; the blood vessel lower boundary of the grayscale image is a boundary in which the pixel value of the center point of a certain row in the grayscale image is less than the first preset pixel value and the pixel value of the center point of the next row in the grayscale image is greater than the first preset pixel value; Step 3.3) Based on the preset features of the region of interest, extract the region of interest including the blood vessel region with a width of the envelope region of the blood vessel greater than 5 mm and the muscle region with a width of 20 mm enveloped from the upper and lower boundaries of the blood vessel region, and the depth of the region of interest is 5-10 cm in the preset sampling line direction, and determine the one-dimensional image conversion range of the preset sampling line according to the extracted region of interest.

6. The method for monitoring deformation and blood flow in lower extremity veins based on M-mode ultrasound technology according to claim 3, characterized in that, In step 4, the specific method for obtaining the motion waveform image of the blood vessel wall and valve position changing with time is as follows: Step 4.1) Determine whether the pixel value of all pixel points in any length pixel strip in the region of interest is less than the first preset pixel value; If there are at least two pixel points in the region of interest that satisfy the requirement that the pixel value is less than the first preset pixel value, calculate the actual distance between the two nearest pixel points that satisfy the requirement to obtain the tissue depth range of the region of interest, and determine whether the distance is greater than the second preset length value; if the distance is greater than the second preset length value, define the low-pixel-value region between the two nearest pixel points that satisfy the requirement as a venous envelope region, and mark it as a "dark line" representing a low-pixel line segment with a pixel value less than the first preset pixel value; Step 4.2) According to the "dark line" identification method described above, obtain all the "dark lines" in the preset sampling line direction, locate the position of the midpoint of the "dark line", switch to the D-mode ultrasound mode of the flexible patch-type ultrasonic probe at this position, and set the sampling volume to 1 / 3 of the width of the "dark line", thereby obtaining the blood flow velocity corresponding to all the "dark lines"; mark the "dark line" with a blood flow peak velocity greater than 20 cm / s as an arterial source signal, and mark the "dark line" with a blood flow peak velocity less than or equal to 20 cm / s as a non-arterial source signal, screen all the echo signals in the preset sampling line direction, and select the preset sampling line corresponding to the non-arterial source signal with the longest "dark line" length as the optimal sampling line, and the direction of the optimal sampling line is taken as the scanning direction of the lower extremity vein deformation monitoring; Step 4.3) After determining the optimal sampling line, record the initial length of the "dark line" in the direction of the optimal sampling line, and record the initial minimum pixel value and the initial maximum pixel value of all pixel points in the "dark line" region, so as to perform image quality control and early warning on the obtained M-mode ultrasound image; Step 4.4) After determining the optimal sampling line, locate the position of the midpoint of the "dark line" in the direction of the optimal sampling line, switch to the D-mode ultrasound mode of the flexible patch-type ultrasonic probe at this position, and set the sampling volume to 1 / 3 of the width of the "dark line" corresponding to the optimal sampling line, thereby obtaining the initial blood flow velocity corresponding to the optimal sampling line, so as to perform image quality control and early warning on the obtained M-mode ultrasound image; Step 4.5) After determining the optimal sampling line, the edge of the nearest and farthest pixels of the "dark line" in the direction of the optimal sampling line is shifted-time integrated to obtain the broken line graph of the deformation of the "dark line" region at both ends of the optimal sampling line with time, which corresponds to the dynamic waveform of the vein lumen; Step 4.6) The part between the adjacent two waveforms in the obtained broken line graph is recorded as a "dark area", and it is screened whether there is a pixel point with a pixel value higher than the first preset pixel value in the "dark area", if there is, then according to the spot detection algorithm, the displacement-time integral of the three pixel points with the highest pixel value in the "dark area" is carried out to obtain the waveform graph of the pixel value of the edge and the internal pixel value of the "dark area" with time, which corresponds to the dynamic waveform of the vein valve; Step 4.7) The dynamic waveform of the vein lumen and the dynamic waveform of the vein valve are manually recorded, and finally the motion waveform image of the vein wall and the depth position of the vein valve in the scanning direction of the user's lower limb vein deformation monitoring is output, and the volume change of the lower limb muscle vein in the short axis direction is calculated.

7. The method for monitoring deformation and blood flow in lower extremity veins based on M-mode ultrasound technology according to claim 1, characterized in that, Also includes: Step 5) The depth and deformation information of the extracted region of interest is measured to obtain analysis parameters including muscle vein area change rate, vein valve dynamic, valve opening time and speed, and vortex area autography.

8. A device for monitoring deformation and blood flow in lower extremity veins using the method of monitoring deformation and blood flow in lower extremity veins based on M-mode ultrasound technology according to any one of claims 1 to 7, characterized in that, Including: A handheld / attached calibration probe is responsible for scanning the standard section of the target blood vessel of the user's lower limb to obtain B-mode ultrasound images of the user's lower limb blood vessels and surrounding tissue regions, which are used for presetting the gray signal gradient condition and the region of interest extraction condition; A preset module is responsible for presetting the gray signal gradient condition and the region of interest extraction condition; A flexible patch type ultrasound probe is responsible for M-mode ultrasound scanning of the user's lower limb skin surface in multiple preset sampling line directions under the user's motion state to obtain at least one M-mode ultrasound image containing the user's lower limb artery and vein wall position and its internal structure information, which is used for one-dimensional image conversion in the later stage; at the same time, it is responsible for D-mode ultrasound sampling of the midpoint position of the "dark line" determined in the preset sampling line direction, which is used to obtain the blood flow velocity corresponding to the "dark line"; A gray module is responsible for converting the M-mode ultrasound image into a corresponding gray image based on the preset gray signal gradient condition, which is used for region of interest extraction; An extraction module is responsible for extracting the region of interest in the M-mode ultrasound image converted into a corresponding gray image based on the preset region of interest extraction condition; A definition module is responsible for judging whether the pixel value of all pixel points in any length pixel strip in the region of interest is less than the first preset pixel value of the gray signal gradient condition; If there are at least two pixels in the region of interest that satisfy the requirement of pixel value being less than the first preset pixel value, the actual distance between the two farthest pixels that satisfy the requirement is calculated to obtain the tissue depth range of the region of interest, and it is determined whether the distance is greater than a second preset length value of the gray signal gradient condition; if the distance is greater than the second preset length value, the low-pixel-value region between the two farthest pixels that satisfy the requirement is defined as a vein envelope region, and is recorded as a "dark line", which represents a low-pixel line segment with a pixel value less than the first preset pixel value; after obtaining all the "dark lines" in the preset sampling line directions, the blood flow velocity measured by the D-mode ultrasonic mode of the flexible patch ultrasonic probe is used to select the preset sampling line corresponding to the non-artery source signal with the longest "dark line" as the optimal sampling line, and the direction of the optimal sampling line is used as the scanning direction of the lower extremity vein deformation monitoring; The integral module is responsible for performing displacement-time integration on the nearest and farthest pixel edges of the "dark line" in the direction of the optimal sampling line after the optimal sampling line is determined, obtaining the broken line graph of the deformation of the two end regions of the "dark line" in the direction of the optimal sampling line over time, and corresponding to the compliance waveform of the vein lumen; then, the part between the adjacent two waveforms in the broken line graph is recorded as a "dark area", and it is determined whether there is a pixel point with a pixel value higher than the first preset pixel value in all the "dark areas"; if there is, displacement-time integration is performed on the three pixel points with the highest pixel values in the "dark area" range that meet the condition according to the spot detection algorithm, to obtain the curve graph of the pixel values of the edges and the internal pixels of the "dark area" over time, corresponding to the compliance waveform of the vein valve; The tracing module is used to provide an operation platform and a display interface for manual tracing of the compliance waveform of the vein lumen and the compliance waveform of the vein valve, and outputs the motion waveform image of the vein wall and the depth position of the vein valve over time in the scanning direction of the lower extremity vein deformation monitoring after tracing; The quality control and early warning module is responsible for recording the initial length of the "dark line", the initial minimum and maximum pixel values of all the pixel points in the "dark line" region, and the initial blood flow velocity corresponding to the optimal sampling line after the optimal sampling line is determined, so as to perform image quality control and early warning on the obtained M-mode ultrasonic image; the motion waveform image of the vein wall and the depth position of the vein valve over time is monitored, and if the amplitude of the compliance waveform of the vein lumen is less than a third preset amplitude value of the gray signal gradient condition, the amplitude of the compliance waveform of the vein valve (or other intraluminal objects) is less than a fourth preset amplitude value of the gray signal gradient condition, or there are more than three pixel points in the selected "dark area" with a pixel value greater than the first preset pixel value, a warning indicator light is turned on and the motion waveform image of the vein wall and the depth position of the vein valve over time is uploaded to the local. The analysis module is responsible for using the output user lower limb vein deformation monitoring scanning direction vein wall and vein valve depth position change with time motion waveform image to calculate the volume change of the lower limb muscle vein in the short axis direction; responsible for measuring the depth and deformation information of the extracted interest region to obtain analysis parameters including muscle vein area change rate, vein valve mobility, valve opening time and speed, and vortex area self-luminous.

9. A computer apparatus, comprising: Comprise: A processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete the communication among each other through the communication bus, the memory is used for depositing at least one executable instruction, and the executable instruction makes the processor execute the operation corresponding to the method for monitoring the lower limb vein deformation and blood flow based on the M-mode ultrasonic technology in any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores at least one executable instruction, and the executable instruction makes the processor execute the operation corresponding to the method for monitoring the lower limb vein deformation and blood flow based on the M-mode ultrasonic technology in any one of claims 1-7.

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