A blood vessel puncture system based on a palm ultrasound device and a puncture needle positioning control method

Abstract

The application provides a kind of vascular puncture system and method based on palm ultrasonic equipment, it is related to puncture guiding technical field, including: obtaining the real-time ultrasound image of the puncture site of patient by palm ultrasonic equipment, and the blood vessel boundary and center line in real-time ultrasound image are identified;According to the blood vessel boundary and center line, the best puncture route is calculated, and then the needle tip position of the puncture needle of the puncture positioning device of palm ultrasonic equipment is adjusted according to the best puncture route to carry out vascular puncture.The beneficial effect is that the puncture positioning device is added in the palm ultrasonic equipment, and the image acquisition module and the puncture module are configured, which not only solves the problem that the traditional system depends on the experience and manual operation skill of medical staff and is easily affected by human factors;Compared with the robot-assisted system, it can not only have very close puncture accuracy and success rate, and the system complexity of the application is low, the cost is low and convenient to carry.

Description

Technical Field

[0001] This invention relates to the field of puncture guidance technology, and in particular to a vascular puncture system and a puncture needle positioning and control method based on a handheld ultrasound device. Background Technology

[0002] In the medical field, vascular puncture is a common and important procedure, widely used in diagnosis, treatment, and emergency care. Traditionally, vascular puncture relies primarily on the experience and skill of medical personnel, performed manually using an ultrasound probe and puncture needle. However, with the continuous advancement of medical technology and the increasing demands of patients, higher requirements have been placed on the accuracy, safety, and efficiency of vascular puncture. Therefore, ultrasound-guided puncture systems have emerged, aiming to assist medical personnel in more accurately locating blood vessels and improving the success rate of punctures through real-time ultrasound imaging technology. Existing technologies include traditional ultrasound-guided puncture systems and robot-assisted ultrasound-guided puncture systems.

[0003] Traditional ultrasound-guided puncture systems mainly consist of an ultrasound probe, a monitor, and a puncture needle. This system acquires real-time ultrasound images of the blood vessel through the probe and displays them on the monitor for observation and operation by medical personnel. However, this system has significant limitations. First, it is highly dependent on the experience and manual skills of the medical personnel, making it prone to errors due to human factors. Second, medical personnel need to simultaneously observe the monitor and manually operate the puncture needle during the procedure, placing high demands on their coordination and concentration. Furthermore, in complex or difficult puncture situations (such as deep vessels or small-diameter vessels), traditional systems often struggle to guarantee accuracy and success rates.

[0004] To overcome the limitations of traditional systems, robot-assisted ultrasound-guided puncture systems have emerged. These systems automate or semi-automate the puncture procedure through robotic arms and control algorithms. The robotic arm precisely controls the movement and angle of the puncture needle, while an ultrasound probe is mounted on the arm to acquire real-time images of the blood vessels. The control system processes the images and executes the control algorithm to achieve automated puncture. However, this system also has some drawbacks. First, its high complexity and cost limit its widespread clinical application. Second, its large size and inconvenience make it unsuitable for bedside use or emergency situations. Furthermore, while robot-assisted systems improve the accuracy and success rate of punctures, specially trained professionals are still required to operate and maintain the system.

[0005] In summary, all existing ultrasound-guided puncture systems have limitations to varying degrees. Traditional systems rely on the experience and manual skills of medical personnel, making them susceptible to human error; while robot-assisted systems improve the accuracy and success rate of punctures, they are complex, expensive, and inconvenient to carry. Summary of the Invention

[0006] To address the problems existing in the prior art, the present invention provides a vascular puncture system based on a handheld ultrasound device, comprising:

[0007] The image acquisition module is used to acquire real-time ultrasound images of the patient's puncture site from the handheld ultrasound device, and to identify the blood vessel boundaries and center line in the real-time ultrasound images.

[0008] The puncture module, connected to the image acquisition module, is used to calculate the optimal puncture route based on the blood vessel boundary and the center line, and then adjust the needle tip position of the puncture positioning device according to the optimal puncture route to perform blood vessel puncture.

[0009] Preferably, the image acquisition module includes:

[0010] The image processing unit is used to acquire real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and to perform image preprocessing on the real-time ultrasound images to obtain preprocessed images.

[0011] The image recognition unit is used to perform image recognition on the preprocessed image using a blood vessel recognition model, identify the blood vessel boundaries of all blood vessels in the preprocessed image, and then, for each identified blood vessel, identify the blood vessel to be punctured according to the selection command input by the medical staff, and calculate the center line of the blood vessel to be punctured.

[0012] Preferably, the image processing unit includes:

[0013] A contrast enhancement subunit is used to adjust the contrast of the real-time ultrasound image using an adaptive contrast network model, and then update the real-time ultrasound image with the contrast-adjusted real-time ultrasound image.

[0014] A resolution reconstruction subunit, connected to the contrast enhancement subunit, is used to perform super-resolution reconstruction of the real-time ultrasound image using an adversarial network model, and then update the real-time ultrasound image with the resolution-reconstructed real-time ultrasound image.

[0015] An image denoising subunit, connected to the resolution reconstruction subunit, is used to perform denoising processing on the real-time ultrasound image using a convolutional neural network, and then update the real-time ultrasound image with the denoised real-time ultrasound image.

[0016] An edge enhancement subunit, connected to the image denoising subunit, is used to perform edge enhancement on the real-time ultrasound image using an edge enhancement network model, and then uses the edge-enhanced real-time ultrasound image as the preprocessed image.

[0017] Preferably, the puncture module includes:

[0018] The path calculation unit is used to receive the puncture initiation area drawn by medical staff on the skin surface in the real-time ultrasound image and the puncture target point in the blood vessel to be punctured. Then, it selects several starting points in the puncture initiation area and connects them with the puncture target point to obtain multiple puncture paths. Then, it filters out the puncture paths that do not intersect with other blood vessels from all the puncture paths. Then, it filters out the puncture path with the smallest angle to the skin surface and less than a preset angle range from each of the puncture paths that do not intersect with other blood vessels as the optimal puncture route.

[0019] The needle adjustment unit, connected to the path calculation unit, is used to move the tip of the puncture needle of the puncture positioning device to the starting point of the optimal puncture route, and adjust the angle between the puncture needle and the skin surface to the angle between the optimal puncture route and the skin surface before performing vascular puncture.

[0020] The present invention also provides a puncture needle positioning control method based on a handheld ultrasound device, applied to the above-mentioned vascular puncture system, comprising:

[0021] Step S1: The vascular puncture system acquires real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and identifies the vascular boundaries and centerline in the real-time ultrasound images.

[0022] In step S2, the vascular puncture system calculates the optimal puncture route based on the vascular boundary and the centerline, and then adjusts the needle tip position of the puncture positioning device according to the optimal puncture route to perform vascular puncture.

[0023] Preferably, step S1 includes:

[0024] Step S11: The vascular puncture system acquires real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and performs image preprocessing on the real-time ultrasound images to obtain preprocessed images.

[0025] In step S12, the vascular puncture system uses a vascular recognition model to perform image recognition on the preprocessed image, identify the vascular boundaries of all blood vessels in the preprocessed image, and then for each identified blood vessel, the blood vessel to be punctured is identified according to the selection command input by the medical staff, and the center line of the blood vessel to be punctured is calculated.

[0026] Preferably, step S11 includes:

[0027] Step S111: The vascular puncture system uses an adaptive contrast network model to adjust the contrast of the real-time ultrasound image, and then updates the real-time ultrasound image with the contrast-adjusted real-time ultrasound image.

[0028] Step S112: The vascular puncture system uses an adversarial network model to perform super-resolution reconstruction of the real-time ultrasound image, and then updates the real-time ultrasound image with the reconstructed resolution image.

[0029] Step S113: The vascular puncture system uses a convolutional neural network to denoise the real-time ultrasound image, and then updates the real-time ultrasound image with the denoised real-time ultrasound image.

[0030] In step S114, the vascular puncture system uses an edge enhancement network model to enhance the edges of the real-time ultrasound image, and then uses the edge-enhanced real-time ultrasound image as the preprocessed image.

[0031] Preferably, step S2 includes:

[0032] Step S21: The vascular puncture system receives the puncture initiation area drawn by the medical staff on the skin surface in the real-time ultrasound image and the puncture target point in the blood vessel to be punctured. Then, several starting points are selected in the puncture initiation area and connected with the puncture target point to obtain multiple puncture paths. Then, the puncture path that does not intersect with other blood vessels is selected from all the puncture paths. Then, the puncture path with the smallest angle to the skin surface and less than a preset angle range is selected from each puncture path that does not intersect with other blood vessels as the optimal puncture route.

[0033] Step S22: The vascular puncture system moves the tip of the puncture needle of the puncture positioning device to the starting point of the optimal puncture route, and adjusts the angle between the puncture needle and the skin surface to the angle between the optimal puncture route and the skin surface before performing vascular puncture.

[0034] The above technical solution has the following advantages or beneficial effects: By adding a puncture positioning device to the handheld ultrasound device and configuring an image acquisition module and a puncture module, the puncture needle in the puncture positioning device is adjusted to perform puncture when the optimal puncture route is obtained by image recognition processing of the ultrasound image. This not only solves the problem that the traditional system relies on the experience and manual operation skills of medical staff and is easily affected by human factors; compared with the robot-assisted system, it can not only have a very close puncture accuracy and success rate, but also the system of the present invention has low complexity, low cost and is easy to carry. Attached Figure Description

[0035] Figure 1 A schematic diagram of a vascular puncture system based on a handheld ultrasound device is shown in a preferred embodiment of the present invention.

[0036] Figure 2 A schematic diagram of the puncture needle positioning device in a preferred embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the puncture process in a preferred embodiment of the present invention;

[0038] Figure 4 A flowchart illustrating a puncture needle positioning control method based on a handheld ultrasound device, as a preferred embodiment of the present invention.

[0039] Figure 5 This is a schematic diagram of a sub-process of step S1 in a preferred embodiment of the present invention.

[0040] Figure 6 This is a schematic diagram of a sub-process of step S11 in a preferred embodiment of the present invention.

[0041] Figure 7 This is a schematic diagram of the sub-process of step S2 in a preferred embodiment of the present invention. Detailed Implementation

[0042] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. The present invention is not limited to this embodiment; other embodiments that conform to the spirit of the present invention may also fall within the scope of the present invention.

[0043] In a preferred embodiment of the present invention, based on the above-mentioned problems existing in the prior art, a vascular puncture system based on a handheld ultrasound device is provided, comprising:

[0044] Image acquisition module 1 is used to acquire real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and identify the blood vessel boundaries and center line in the real-time ultrasound image.

[0045] The puncture module 2 is connected to the image acquisition module 1. It is used to calculate the optimal puncture route based on the blood vessel boundary and center line, and then adjust the needle tip position of the puncture positioning device according to the optimal puncture route to perform blood vessel puncture.

[0046] Specifically, in this embodiment, a puncture positioning device 100 is added to the handheld ultrasound device. The handheld ultrasound device is equipped with an image acquisition module 1 and a puncture module 2. When the ultrasound image is processed by image recognition to obtain the optimal puncture route, the puncture needle in the puncture positioning device is adjusted to perform the puncture. This not only solves the problem that traditional systems rely on the experience and manual operation skills of medical personnel and are easily affected by human factors, but also achieves a very close accuracy and success rate of puncture compared to robot-assisted systems. Furthermore, the system of this invention has low complexity, low cost, and is easy to carry.

[0047] In this embodiment, the puncture needle positioning device 100 is installed on the ultrasound probe of a handheld ultrasound device. Specifically, it includes a position adjustment structure 110 and a propulsion mechanism. The position adjustment mechanism is mainly used to adjust the position of the puncture point on the patient's skin surface and the angle of the puncture needle. Figure 2 As shown, it includes a two-axis drive mechanism 1110 and an angle adjustment mechanism 1120 fixed on the two-axis drive structure. The two drive mechanisms are used to adjust the position of the puncture point of the puncture needle tip 120 on the patient's skin surface, and the angle adjustment mechanism is used to change the tilt angle of the puncture needle to change the angle between the puncture needle and the skin surface. The propulsion mechanism is mainly used to push the puncture needle into the patient's skin for vascular puncture after the puncture point and the optimal puncture route have been determined.

[0048] In a preferred embodiment of the present invention, the image acquisition module 1 includes:

[0049] Image processing unit 11 is used to acquire real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and to perform image preprocessing on the real-time ultrasound images to obtain preprocessed images.

[0050] The image recognition unit 12 is used to perform image recognition on the preprocessed image using a blood vessel recognition model, identify the blood vessel boundaries of all blood vessels in the preprocessed image, and then for each identified blood vessel, identify the blood vessel to be punctured according to the selection command input by the medical staff, and calculate the center line of the blood vessel to be punctured.

[0051] In this embodiment, the image processing unit 11 includes:

[0052] The contrast enhancement subunit 111 is used to adjust the contrast of a real-time ultrasound image using an adaptive contrast network model, and then update the real-time ultrasound image to the contrast-adjusted real-time ultrasound image.

[0053] The resolution reconstruction subunit 112 is connected to the contrast enhancement subunit 111 and is used to perform super-resolution reconstruction of real-time ultrasound images using an adversarial network model, and then update the real-time ultrasound images to the resolution-reconstructed real-time ultrasound images.

[0054] The image denoising subunit 113 is connected to the resolution reconstruction subunit 112 and is used to perform denoising processing on the real-time ultrasound image using a convolutional neural network, and then update the real-time ultrasound image to the denoised real-time ultrasound image.

[0055] The edge enhancement subunit 114 is connected to the image denoising subunit 113 and is used to perform edge enhancement on the real-time ultrasound image using the edge enhancement network model. Then, the edge-enhanced real-time ultrasound image is used as the preprocessed image.

[0056] Specifically, in the medical practice of vascular puncture, the application of an image processing unit can significantly improve the accuracy and safety of ultrasound-guided vascular puncture. The following is a specific example illustrating how the aforementioned image processing unit functions during vascular puncture:

[0057] Example Background

[0058] During vascular punctures (such as central venous catheterization and arterial blood sampling), doctors rely on ultrasound images to locate blood vessels and ensure that the puncture needle accurately enters the target vessel. However, traditional ultrasound images may be affected by problems such as low contrast, insufficient resolution, and noise interference, resulting in blurred vessel boundaries and increasing the difficulty and risk of puncture.

[0059] Image processing unit application steps

[0060] During the preparation phase for vascular puncture, the doctor first obtains real-time ultrasound images of the patient.

[0061] The contrast enhancement subunit uses an adaptive contrast network model to process the image and automatically adjust the contrast between blood vessels and surrounding tissues in the image, making the blood vessel boundaries clearer.

[0062] The updated images are displayed on the ultrasound screen, making it easier for doctors to identify the location and depth of blood vessels.

[0063] Next, the resolution reconstruction subunit uses an adversarial network model to perform super-resolution reconstruction on the already contrast-enhanced image.

[0064] By learning the features of a large number of high-resolution images, the model is able to generate ultrasound images with higher resolution and more detail, further refining vascular structures and reducing blurring and artifacts.

[0065] The improved image resolution provides doctors with more detailed information about the vascular structure, which helps to plan the puncture path more accurately.

[0066] Noise may be introduced during image transmission or acquisition, affecting image quality.

[0067] The image denoising subunit uses a convolutional neural network to denoise the image, effectively removing random noise and speckle noise while maintaining the integrity and clarity of the blood vessel contour.

[0068] The denoised images are cleaner and smoother, providing doctors with clearer visual guidance.

[0069] Finally, the edge enhancement subunit uses an edge enhancement network model to further process the image.

[0070] This model can enhance the contrast of blood vessel edges, making the blood vessel outline more prominent and improving the visual effect and readability of the image.

[0071] In images enhanced with edge detection, the boundary between blood vessels and surrounding tissues becomes clearer, allowing doctors to more accurately determine the puncture point and direction.

[0072] Through the integrated application of the aforementioned image processing units, doctors can obtain clearer, more accurate, and higher-resolution ultrasound images during vascular puncture. This not only improves the success rate of punctures but also reduces the risk of complications caused by mispunctures. Simultaneously, the automation and intelligence of image processing technology also reduce the workload of doctors and improve the efficiency and quality of medical services.

[0073] After image preprocessing, it is necessary to identify the vessel boundaries and center lines of the blood vessels in the image.

[0074] The pre-processed images are updated and displayed on the screen of the ultrasound equipment for further analysis and operation by medical staff.

[0075] The image recognition unit receives the preprocessed image and performs image recognition using a blood vessel recognition model. This model has been extensively trained and is capable of automatically recognizing blood vessel structures in the image and marking the boundaries of the blood vessels.

[0076] For each identified blood vessel, the image recognition unit further calculates its centerline. The centerline calculation is based on the boundary information of the blood vessel, and the geometric center path of the blood vessel is obtained through algorithm processing.

[0077] In this step, during the calculation of the vessel centerline, the image recognition unit utilizes the vessel's boundary information and extracts the geometric center path of the vessel through a series of image processing and algorithmic analysis steps. The following is a specific example illustrating this centerline calculation process:

[0078] Background of the Example: In ultrasound images, blood vessels typically appear as dark areas of a certain width and length, their boundaries formed by the contrast difference between the vessel wall and the surrounding tissue. For precise vascular puncture or other medical procedures, it is necessary to determine the centerline of the vessel, i.e., the geometric center path of the vessel.

[0079] Centerline calculation process:

[0080] 1. Boundary extraction:

[0081] The image recognition unit first processes the pre-processed ultrasound image using an edge detection algorithm (such as the Canny edge detector) to extract the boundaries of the blood vessels. This step generates a binary image in which the blood vessel boundaries are marked in white (or highlighted), and the rest is black (or underexposed).

[0082] 2. Boundary refinement:

[0083] Next, the extracted vessel boundaries are refined. Refinement algorithms (such as the Zhang-Suen refinement algorithm) are used to reduce the boundary pixels to a single pixel width, forming the skeleton of the vessel. The result of this step is a thinner line that roughly represents the center of the vessel, but may contain some burrs and branches.

[0084] 3. Centerline extraction:

[0085] The refined skeleton requires further processing to extract a smooth centerline. This typically involves steps such as deburring, smoothing curves, and handling branch points.

[0086] A common approach is to use morphological manipulations (such as erosion and dilation) to smooth the skeletal lines and to use connectivity analysis to identify and manage branching points. At branching points, major branches can be selected or certain branches can be ignored based on the actual morphology of the vessel and the puncture requirements.

[0087] Another approach is to use graph theory or path search algorithms (such as Dijkstra's algorithm or A* algorithm) to search for the shortest or optimal path from one end of the blood vessel to the other on the skeleton. This path is the desired centerline.

[0088] 4. Post-processing:

[0089] Finally, the extracted centerline undergoes post-processing to ensure its smoothness and accuracy. This may include removing isolated short segments, smoothing minor ripples on the curve, and adjusting the centerline's position to better reflect the geometric center of the blood vessel.

[0090] After the above processing steps, the image recognition unit outputs one or more smooth curves, which represent the geometric center path of the blood vessels in the ultrasound image. Medical staff can use this centerline information to plan the puncture path, ensuring that the puncture needle enters along the center of the blood vessel, thereby improving the accuracy and safety of the puncture.

[0091] It should be noted that since the morphology of blood vessels and the quality of ultrasound images may vary from patient to patient, in practical applications, it may be necessary to adjust and optimize the algorithm parameters according to the specific situation to obtain the best centerline extraction effect.

[0092] Furthermore, based on the vascular images and centerline information displayed on the ultrasound equipment screen, medical staff input selection commands to identify the vessel to be punctured. This is typically done via a touchscreen or external controller, allowing medical staff to select the clearest, straightest, and easiest-to-puncture vessel as the target.

[0093] The blood vessel to be punctured is clearly marked, and its center line is clearly visible. This provides precise visual guidance for subsequent puncture procedures.

[0094] By employing an image acquisition module that includes image processing and image recognition units, the vascular puncture process becomes more precise, efficient, and safe. Medical staff can visually visualize the boundaries and centerline of the blood vessel, making it easier to select the optimal puncture point and path. This not only improves the success rate of punctures but also reduces the risk of complications due to mispuncture. Simultaneously, the module reduces the workload of medical staff and improves the efficiency and quality of medical services.

[0095] In a preferred embodiment of the present invention, the puncture module 2 includes:

[0096] The path calculation unit 21 is used to receive the puncture starting area drawn by medical staff on the skin surface in the real-time ultrasound image and the puncture target point in the blood vessel to be punctured. Then, several starting points are selected in the puncture starting area and connected with the puncture target point to obtain multiple puncture paths. Then, the puncture path that does not cross other blood vessels is selected from all the puncture paths. Then, the puncture path with the smallest angle with the skin surface and less than the preset angle range is selected from each puncture path that does not cross other blood vessels as the best puncture route.

[0097] The needle adjustment unit 22 is connected to the path calculation unit 21. It is used to move the tip of the puncture needle of the puncture positioning device to the starting point of the optimal puncture route and adjust the angle between the puncture needle and the skin surface to the angle between the optimal puncture route and the skin surface before performing vascular puncture.

[0098] Specifically, in the process of vascular puncture, the application of a puncture module that includes a path calculation unit and a needle adjustment unit can greatly improve the accuracy and safety of the puncture. The following is a specific embodiment illustrating the application of these modules during vascular puncture:

[0099] Patients require precise vascular puncture procedures, such as central venous catheterization. Healthcare professionals use a puncture system that incorporates real-time ultrasound imaging, which includes an image processing unit, an image recognition unit, and a puncture module.

[0100] 1. Application of Path Calculation Unit

[0101] Step 1: Select the puncture starting area and target point

[0102] Medical staff can use the touchscreen or external controller of the ultrasound equipment to delineate a puncture initiation area on the patient's skin surface in a real-time ultrasound image.

[0103] At the same time, select a clear puncture target point inside the blood vessel to be punctured. This point is usually the center of the blood vessel or an easy-to-puncture site.

[0104] Step 2: Generate and filter puncture paths

[0105] After receiving information about the starting area and the target point, the path calculation unit automatically selects several starting points within the starting area and connects them with the target point to generate multiple possible puncture paths.

[0106] Subsequently, the path calculation unit uses the blood vessel boundary information provided by the image processing unit to filter out puncture paths that do not intersect with other blood vessels.

[0107] Among these non-intersecting paths, the path with the smallest angle to the skin surface and less than a preset angle range (such as 30 degrees) is further selected as a candidate path.

[0108] Ultimately, the path with the smallest angle that meets all the conditions is selected as the optimal puncture route.

[0109] 2. Application of the needle adjustment unit

[0110] Step 3: Adjust the position of the puncture needle

[0111] The needle adjustment unit receives the optimal puncture route information calculated by the path calculation unit, including the starting point position and puncture angle.

[0112] The needle adjustment unit drives the puncture positioning device (the two-axis drive mechanism and the angle adjustment mechanism fixed on the two-axis drive structure in the aforementioned embodiments) to precisely move the tip of the puncture needle to the starting point of the optimal puncture route.

[0113] Step 4: Adjust the puncture angle

[0114] The needle adjustment unit is also responsible for adjusting the angle between the puncture needle and the skin surface, ensuring that this angle is consistent with the angle between the optimal puncture route and the skin surface.

[0115] After the adjustment is completed, as follows: Figure 3 As shown, the puncture needle is positioned at the puncture point B of the optimal puncture route in the starting area A and at the angle α with the skin, and the puncture operation is performed towards the puncture target point C.

[0116] Step 5: Perform the puncture procedure

[0117] After confirming that the position and angle of the puncture needle are correct, the medical staff will begin the puncture procedure.

[0118] The puncture needle enters the blood vessel along the optimal puncture route. Due to the precise path planning and appropriate angle, the puncture process is smoother and safer.

[0119] Implementation Results: By applying a puncture module that includes a path calculation unit and a needle adjustment unit, the vascular puncture process has become more intelligent and precise. Medical staff no longer need to rely on experience and feel for punctures; instead, they rely on the optimal puncture route and precise angle adjustments provided by the system. This not only improves the success rate of punctures but also reduces the risk of complications caused by mispunctures. At the same time, the application of this module also reduces the workload of medical staff and improves the efficiency and quality of medical services.

[0120] This invention also provides a puncture needle positioning control method based on a handheld ultrasound device, applicable to the aforementioned vascular puncture system, such as... Figure 4 As shown, it includes:

[0121] Step S1: The vascular puncture system acquires real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and identifies the vascular boundaries and centerline in the real-time ultrasound images.

[0122] In step S2, the vascular puncture system calculates the optimal puncture route based on the vascular boundary and centerline, and then adjusts the needle tip position of the puncture positioning device according to the optimal puncture route to perform vascular puncture.

[0123] In a preferred embodiment of the present invention, such as Figure 5 As shown, step S1 includes:

[0124] Step S11: The vascular puncture system acquires real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and performs image preprocessing on the real-time ultrasound images to obtain preprocessed images.

[0125] In step S12, the vascular puncture system uses a vascular recognition model to perform image recognition on the preprocessed image, identify the vascular boundaries of all blood vessels in the preprocessed image, and then for each identified blood vessel, the blood vessel to be punctured is identified according to the selection command input by the medical staff, and the center line of the blood vessel to be punctured is calculated.

[0126] In a preferred embodiment of the present invention, such as Figure 6 As shown, step S11 includes:

[0127] Step S111: The vascular puncture system uses an adaptive contrast network model to adjust the contrast of the real-time ultrasound image, and then updates the real-time ultrasound image to the contrast-adjusted real-time ultrasound image.

[0128] In step S112, the vascular puncture system uses an adversarial network model to perform super-resolution reconstruction of the real-time ultrasound image, and then updates the real-time ultrasound image to the reconstructed real-time ultrasound image.

[0129] Step S113: The vascular puncture system uses a convolutional neural network to denoise the real-time ultrasound image, and then updates the real-time ultrasound image with the denoised real-time ultrasound image.

[0130] In step S114, the vascular puncture system uses an edge enhancement network model to enhance the edges of the real-time ultrasound image, and then uses the edge-enhanced real-time ultrasound image as the preprocessed image.

[0131] In a preferred embodiment of the present invention, such as Figure 7 As shown, step S2 includes:

[0132] Step S21: The vascular puncture system receives the puncture starting area drawn by medical staff on the skin surface in the real-time ultrasound image and the puncture target point in the blood vessel to be punctured. Then, several starting points are selected in the puncture starting area and connected with the puncture target point to obtain multiple puncture paths. Then, the puncture path that does not intersect with other blood vessels is selected from all the puncture paths. Then, the puncture path with the smallest angle with the skin surface and less than the preset angle range is selected from each puncture path that does not intersect with other blood vessels as the best puncture route.

[0133] In step S22, the vascular puncture system moves the tip of the puncture needle of the puncture positioning device to the starting point of the optimal puncture route, and adjusts the angle between the puncture needle and the skin surface to the angle between the optimal puncture route and the skin surface before performing vascular puncture.

[0134] The above are merely preferred embodiments of the present invention and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should recognize that any equivalent substitutions and obvious changes made using the content of this specification and illustrations should be included within the protection scope of the present invention.

Claims

1. A vascular puncture system based on a handheld ultrasound device, characterized in that, include: The image acquisition module is used to acquire real-time ultrasound images of the patient's puncture site from the handheld ultrasound device, and to identify the blood vessel boundaries and center line in the real-time ultrasound images. The puncture module, connected to the image acquisition module, is used to calculate multiple puncture paths that do not intersect with other blood vessels based on the blood vessel boundary and the center line. Then, the puncture path with the smallest angle to the skin surface and less than a preset angle range is selected from the puncture paths as the optimal puncture route. Then, the needle tip position of the puncture needle of the handheld ultrasound device is adjusted according to the optimal puncture route to perform blood vessel puncture. The puncture positioning device includes an angle adjustment mechanism, which is used to adjust the angle between the puncture needle and the skin surface to the angle between the optimal puncture route and the skin surface.

2. The vascular puncture system according to claim 1, characterized in that, The image acquisition module includes: The image processing unit is used to acquire real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and to perform image preprocessing on the real-time ultrasound images to obtain preprocessed images. The image recognition unit is used to perform image recognition on the preprocessed image using a blood vessel recognition model, identify the blood vessel boundaries of all blood vessels in the preprocessed image, and then, for each identified blood vessel, identify the blood vessel to be punctured according to the selection command input by the medical staff, and calculate the center line of the blood vessel to be punctured.

3. The vascular puncture system according to claim 2, characterized in that, The image processing unit includes: A contrast enhancement subunit is used to adjust the contrast of the real-time ultrasound image using an adaptive contrast network model, and then update the real-time ultrasound image with the contrast-adjusted real-time ultrasound image. A resolution reconstruction subunit, connected to the contrast enhancement subunit, is used to perform super-resolution reconstruction of the real-time ultrasound image using an adversarial network model, and then update the real-time ultrasound image with the resolution-reconstructed real-time ultrasound image. An image denoising subunit, connected to the resolution reconstruction subunit, is used to perform denoising processing on the real-time ultrasound image using a convolutional neural network, and then update the real-time ultrasound image with the denoised real-time ultrasound image. An edge enhancement subunit, connected to the image denoising subunit, is used to perform edge enhancement on the real-time ultrasound image using an edge enhancement network model, and then uses the edge-enhanced real-time ultrasound image as the preprocessed image.

4. The vascular puncture system according to claim 2, characterized in that, The puncture module includes: The path calculation unit is used to receive the puncture initiation area drawn by medical staff on the skin surface in the real-time ultrasound image and the puncture target point in the blood vessel to be punctured. Then, it selects several starting points in the puncture initiation area and connects them with the puncture target point to obtain multiple puncture paths. Then, it filters out the puncture paths that do not intersect with other blood vessels from all the puncture paths. Then, it filters out the puncture path with the smallest angle to the skin surface and less than a preset angle range from each of the puncture paths that do not intersect with other blood vessels as the optimal puncture route. The needle adjustment unit, connected to the path calculation unit, is used to move the tip of the puncture needle of the puncture positioning device to the starting point of the optimal puncture route, and adjust the angle between the puncture needle and the skin surface to the angle between the optimal puncture route and the skin surface before performing vascular puncture.

5. A method for positioning and controlling a puncture needle based on a handheld ultrasound device, characterized in that, The system applied to the vascular puncture system as described in any one of claims 1-4 includes: Step S1: The vascular puncture system acquires real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and identifies the vascular boundaries and centerline in the real-time ultrasound images. In step S2, the vascular puncture system calculates the optimal puncture route based on the vascular boundary and the centerline, and controls the puncture positioning device to automatically adjust the position and angle of the puncture needle tip to a ready state that matches the optimal puncture route.

6. The puncture needle positioning control method according to claim 5, characterized in that, Step S1 includes: Step S11: The vascular puncture system acquires real-time ultrasound images of the patient's puncture site from the handheld ultrasound device and performs image preprocessing on the real-time ultrasound images to obtain preprocessed images. In step S12, the vascular puncture system uses a vascular recognition model to perform image recognition on the preprocessed image, identify the vascular boundaries of all blood vessels in the preprocessed image, and then for each identified blood vessel, the blood vessel to be punctured is identified according to the selection command input by the medical staff, and the center line of the blood vessel to be punctured is calculated.

7. The puncture needle positioning and control method according to claim 6, characterized in that, Step S11 includes: Step S111: The vascular puncture system uses an adaptive contrast network model to adjust the contrast of the real-time ultrasound image, and then updates the real-time ultrasound image with the contrast-adjusted real-time ultrasound image. Step S112: The vascular puncture system uses an adversarial network model to perform super-resolution reconstruction of the real-time ultrasound image, and then updates the real-time ultrasound image with the reconstructed resolution image. Step S113: The vascular puncture system uses a convolutional neural network to denoise the real-time ultrasound image, and then updates the real-time ultrasound image with the denoised real-time ultrasound image. In step S114, the vascular puncture system uses an edge enhancement network model to enhance the edges of the real-time ultrasound image, and then uses the edge-enhanced real-time ultrasound image as the preprocessed image.

8. The puncture needle positioning control method according to claim 6, characterized in that, Step S2 includes: Step S21: The vascular puncture system receives the puncture initiation area drawn by the medical staff on the skin surface in the real-time ultrasound image and the puncture target point in the blood vessel to be punctured. Then, several starting points are selected in the puncture initiation area and connected with the puncture target point to obtain multiple puncture paths. Then, the puncture path that does not intersect with other blood vessels is selected from all the puncture paths. Then, the puncture path with the smallest angle with the skin surface and less than a preset angle range is selected from each puncture path that does not intersect with other blood vessels as the optimal puncture route. In step S22, the vascular puncture system moves the tip of the puncture needle of the puncture positioning device to the starting point of the optimal puncture route and adjusts the angle between the puncture needle and the skin surface to a preparatory state that matches the optimal puncture route.

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