Precise, traceless and high survival rate hair transplantation system and method
By designing a subtle traceless high survival rate hair transplant system in hair transplant technology, the problems of manual judgment errors and unknown hair survival in the prior art are solved, and more efficient and personalized transplantation effects are achieved.
Patent Information
- Application Number
- CN202411681654.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-22
- Publication Date
- 2025-04-04
AI Technical Summary
The existing hair transplant technology relies on manual judgment, which is prone to errors and cannot be sure of the survival of hair after transplantation, resulting in unsatisfactory planting results.
A subtle traceless high survival rate hair transplant system is designed, including a hair data collection module, a hair analysis module, a personalized transplant plan generation module, a history storage module and a planting effect evaluation module. Through the coordinated work of these modules, a personalized transplant plan is generated and the planting effect is evaluated.
By intelligently recommending the most suitable planting plan, the success rate and effect of planting are improved, dissatisfaction and rework after planting are reduced, and user satisfaction and overall quality of planting effect are improved.
Smart Images
Figure CN119763776A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of hair transplantation, and in particular to a system and method for fine, traceless and high survival rate hair transplantation. Background Art
[0002] Hair transplantation, also known as hair transplantation or hair planting, is a cosmetic surgery that uses microsurgical techniques to remove healthy hair follicle tissue, which is then processed and cultured and then artistically transplanted to the bald or hair loss areas of the patient in accordance with the natural hair growth direction. The existing hair transplantation technology often requires doctors to determine the hair transplantation plan suitable for the current user based on the amount of hair on the user's head. However, the method based on manual judgment is prone to errors and it is impossible to know whether the transplanted hair can survive, resulting in less than ideal transplantation effect. In this regard, we propose a precise, traceless, and high survival rate hair transplantation system and method. Summary of the invention
[0003] In order to solve the above technical problems, a precise, traceless and high survival rate hair transplantation system and method are provided. This technical solution solves the above problems.
[0004] In order to achieve the above objectives, the technical solution adopted by the present invention is: a fine and traceless hair transplantation system with high survival rate, the hair transplantation system includes: a hair data collection module, a hair analysis module, a personalized transplantation plan generation module, a history record storage module and a transplantation effect evaluation module; The hair data collection module is used to collect the user's hair data and upload the data to the hair analysis module; The hair analysis module is used to analyze the acquired hair data, determine the current head hair condition of the user, and upload the condition data to the personalized planting plan generation module; The personalized planting plan generation module is used to generate a planting plan suitable for the current user according to the head hair condition of the current user; The historical record storage module is used to store historical analysis data to make decisions for subsequent hair analysis and transplantation; The implantation effect evaluation module evaluates the survival status and implantation effect of the current user's hair after implantation based on the generated implantation plan.
[0005] Preferably, the data collected by the hair data collection module includes hair follicle data and hair sparseness data, wherein the hair coefficient data is collected based on images, and the collection step is performed by aiming the camera at the user's head to shoot, and the photographed head includes the temples, forehead and top of the head, to obtain the user's head image data, and the hair follicle data is collected based on manual acquisition, and the user's current hair is cut off to obtain a hair sample for analysis, and the acquired data is uploaded to the hair analysis module for analysis.
[0006] Preferably, the hair analysis module analyzes the area where the user's hair is sparse in the acquired image data based on the image analysis module, and determines the estimated number of transplanted hair for the current area; the hair sample analysis includes the health status analysis and hair quality analysis of the hair follicles, and the hair samples are viewed based on professional instruments to generate a test report.
[0007] Preferably, the acquired image data is processed for clarity. After clarity, the image data is amplified by 50 times. The image is identified and distinguished between normal hair follicles and atrophic hair follicles based on edge detection, and the number of hairs per square centimeter is calculated. The calculation formula for the number of hairs per square centimeter is:
[0008] Where A is the number of hairs per square centimeter, B is the hair data in the enlarged area of the image, and S is the area of the enlarged area of the current image; The analyzed user hair condition data is uploaded to the personalized planting plan generation module, and the planting plan is generated based on the user's current hair condition.
[0009] Preferably, the personalized implantation plan generation module classifies the user's hair based on the acquired data. The hair classification includes the cases of less hair volume, more hair volume and medium hair volume. The classification is based on the threshold value of the hair volume obtained by big data. The value of the current user analyzed by the hair analysis module is compared with the acquired threshold value, so as to classify the hair situation of the current user. According to different classification results, a personalized implantation plan is generated for the user. The acquired threshold is assumed to be C, and the threshold C is further divided into two endpoint values, C1 and C2. The acquired user hair volume data is D. The comparison form is: if D>C2, the current user's hair volume is classified as more hair volume. If D<C1, the current user's hair volume is classified as more hair volume. Continue to judge. If C1<D<C2, the current user's hair volume is classified as medium hair volume. Different implantation plans are given for users with different hair volume conditions. Based on the implantation data stored in the historical record storage module, the currently selected implantation plan is optimized.
[0010] Preferably, according to the data analysis results, combined with the patient's hair loss situation and expected effect, the planting area is accurately divided and the planting density is adjusted to ensure that the hair is evenly and naturally distributed; the planting plan optimization optimizes the planting technology for users by evaluating the performance of different technologies in similar situations based on historical data. For patients with a large hair loss area but sufficient hair follicle resources in the donor area, FUE technology is selected to reduce postoperative scars. For patients with a small hair loss area but poor hair follicle quality, microtransplantation technology is used. The natural growth direction and angle information of the hair in the data analysis results are used to optimize the hair follicle planting angle and direction in the planting plan to ensure that the transplanted hair appears natural and beautiful.
[0011] Preferably, the implantation effect evaluation module is based on a discrete elastic rod model to simulate the growth effect of the current user's hair after implantation and evaluate the effect of the current implantation plan after implantation. The discrete elastic rod model regards the implanted hair as a structure composed of rigid segments connected by elastic connections. Each node has a degree of freedom, including position and direction, and the elastic connection simulates the bending and torsional stiffness inside the hair to simulate the user's hair implantation effect after implantation and make an evaluation.
[0012] Preferably, when simulating the dynamic behavior of hair, a dynamic equation is established, and the equation form is:
[0013] where F i is the resultant force acting on node i, k ij is the elastic coefficient matrix between nodes i and j, r i With r j is the position vector of nodes i and j, y i is the external force acting on i, i is the hair after implantation. After establishment, the established equation is solved by the iteration method. The evaluation of the implantation effect is based on the comparison between the simulation results and the user's expectations. The comparison includes the overall appearance, density, directional distribution and naturalness of the hair. By adjusting the parameters in the implantation plan, including the implantation density, angle and depth, and re-simulating, the implantation effect can be continuously optimized to achieve user satisfaction.
[0014] Preferably, the history record storage module is used to store the data in the hair transplantation system and save the data based on cloud storage.
[0015] The precise and traceless hair transplantation method with high survival rate includes the following steps: S1. The doctor collects the user's hair data and uploads the collected data; S2, analyzing the collected data to determine the current head hair condition of the user; S3, uploading the judgment result to the personalized planting plan generation module, and recommending a suitable planting plan according to the specific hair condition of the user; S4. Evaluate the hair after implantation according to the current implantation plan, obtain the estimated result after implantation, and check whether it meets the user's needs. If it meets the user's needs, implantation is performed according to the current implantation plan. If it does not meet the user's needs, modify the implantation parameters in the implantation plan and continue the simulation until the user's needs are met; S5. Transplant the user's hair according to the established transplantation plan, and save the data parameters in the process to support subsequent decision-making.
[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention can intelligently recommend the most suitable implantation plan according to the specific hair condition of the user, thereby helping to avoid blind implantation and over-development, thereby improving the success rate and effect of implantation. The currently selected implantation plan is evaluated through the implantation effect evaluation module to ensure that the currently selected implantation plan parameters meet the user's needs. Through pre-evaluation and adjustment, dissatisfaction and rework after implantation are reduced, thereby improving user satisfaction and the overall quality of the implantation effect, effectively simulating the hair effect after implantation, improving the implantation effect, and bringing convenience. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 This is a block diagram of the hair transplantation system of the present invention; Figure 2 The figure is a flow chart of the hair transplantation steps of the present invention. DETAILED DESCRIPTION
[0018] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.
[0019] Reference Figure 1 As shown, the fine and traceless hair transplantation system with high survival rate includes: a hair data collection module, a hair analysis module, a personalized transplantation plan generation module, a historical record storage module and a transplantation effect evaluation module; The hair data collection module is used to collect the user's hair data and upload the data to the hair analysis module; The hair analysis module is used to analyze the acquired hair data, determine the current head hair condition of the user, and upload the condition data to the personalized planting plan generation module; The personalized planting plan generation module is used to generate a planting plan suitable for the current user according to the head hair condition of the current user; The historical record storage module is used to store historical analysis data to make decisions for subsequent hair analysis and transplantation; The implantation effect evaluation module evaluates the survival status and implantation effect of the current user's hair after implantation based on the generated implantation plan.
[0020] The personalized implantation plan generation module of this application customizes the most suitable implantation plan based on the user's unique hair condition. This personalized plan not only improves the treatment effect, but also enhances the safety and comfort of the treatment. The implantation effect evaluation module can track the survival and growth effect of the hair after implantation in real time, and provide timely feedback to the doctor, which helps the doctor to adjust the follow-up care and treatment plan to ensure the optimization of the treatment effect. Due to the personalization and accuracy of the treatment plan, the patient can feel a more natural and satisfactory implantation effect. At the same time, the transparency and patient participation of the system also enhance the patient's trust and satisfaction. The historical record storage module provides doctors with rich data support, enabling doctors to make more scientific decisions based on historical data and experience. The data accumulation and analysis in the system provide strong support for the innovation of hair implantation technology, and doctors and researchers can conduct more in-depth research based on these data.
[0021] The data collected by the hair data acquisition module include hair follicle data and hair sparseness data, among which the hair coefficient data is collected based on images. The collection step is to aim the camera at the user's head to shoot the head, including the temples, forehead and top of the head, to obtain the user's head image data. The hair follicle data is collected based on manual acquisition. The user's current hair is cut off to obtain hair samples for analysis, and the obtained data is uploaded to the hair analysis module for analysis.
[0022] The present application obtains hair thinning data by capturing images of the user's head with a camera, without directly contacting the user's scalp, thereby reducing the user's discomfort and improving the comfort, comprehensiveness and accuracy of data collection. By capturing images of multiple areas of the head, the hair distribution of the user's head can be fully reflected, providing more accurate data support for subsequent hair analysis. The image acquisition method is fast and convenient, and a large amount of data can be collected in a short time, thereby improving the efficiency of data collection. By manually cutting the user's current hair sample, hair follicle information can be directly obtained. This direct acquisition method is more accurate and reliable than indirect analysis.
[0023] The hair analysis module analyzes the areas where the user's hair is sparse in the acquired image data based on the image analysis module, and determines the estimated number of transplanted hair in the current area; the hair sample analysis includes the health status analysis and hair quality analysis of the hair follicles, and the hair samples are viewed based on professional instruments to generate a test report.
[0024] The acquired image data is processed for clarity. After clarity, the image data is amplified by 50 times. The image is identified and distinguished between normal hair follicles and atrophic hair follicles based on edge detection, and the number of hairs per square centimeter is calculated. The calculation formula for the number of hairs per square centimeter is:
[0025] Where A is the number of hairs per square centimeter, B is the hair data in the enlarged area of the image, and S is the area of the enlarged area of the current image; The analyzed user hair condition data is uploaded to the personalized planting plan generation module, and the planting plan is generated based on the user's current hair condition.
[0026] The image analysis module in the present application is prior art and will not be elaborated on here. The step of clarifying the acquired image data is to grayscale the image, eliminate the noise in the image after processing, and then improve the contrast of the image. The edge detection method is used to highlight the edge information in the image, including the outline of the hair, and the hair area and the background area in the image are separated. The separated hair is morphologically processed, the image is restored, and the clarity is processed.
[0027] The personalized implantation plan generation module classifies the user's hair based on the acquired data. The hair classification includes less hair volume, more hair volume and medium hair volume. The classification is based on the threshold value of the hair volume obtained from big data. The value of the current user analyzed by the hair analysis module is compared with the acquired threshold value to classify the hair situation of the current user. According to different classification results, a personalized implantation plan is generated for the user. Suppose the acquired threshold is C, and the threshold C is further divided into two endpoint values, C1 and C2. The acquired user hair volume data is D. The comparison form is: if D>C2, the current user's hair volume is classified as more hair volume. If D<C1, the current user's hair volume is classified as more hair volume. Continue to judge. If C1<D<C2, the current user's hair volume is classified as medium hair volume. Different implantation plans are given for users with different hair volume conditions; based on the implantation data stored in the historical record storage module, the currently selected implantation plan is optimized.
[0028] This application divides the hair volume into three categories: "slight hair volume", "medium hair volume" and "heavy hair volume". The module can provide highly personalized implantation plans for each user's specific situation. This precise customization ensures the pertinence and effectiveness of the treatment plan. Different implantation plans are designed for users with different hair volumes, which can more effectively solve the user's hair loss or insufficient hair volume problems. Through the thresholds C, C1 and C2 determined by big data analysis, the module can automatically judge the user's hair volume, thereby avoiding the subjectivity and uncertainty of manual judgment, which not only improves the accuracy of the judgment.
[0029] According to the data analysis results, combined with the patient's hair loss situation and expected effect, the planting area is accurately divided and the planting density is adjusted to ensure that the hair is evenly and naturally distributed. The planting plan is optimized by evaluating the performance of different technologies in similar situations based on historical data to optimize the planting technology for users. For patients with a large hair loss area but sufficient hair follicle resources in the donor area, FUE technology is selected to reduce postoperative scars. For patients with a small hair loss area but poor hair follicle quality, microtransplantation technology is used. The natural growth direction and angle information of the hair in the data analysis results are used to optimize the hair follicle planting angle and direction in the planting plan to ensure that the transplanted hair appears natural and beautiful.
[0030] This application accurately divides the planting area and adjusts the planting density to ensure that the hair is evenly and naturally distributed, avoiding the appearance of "patches" or uneven sparseness. At the same time, it uses the natural growth direction and angle information of the hair in the data analysis results to optimize the angle and direction of hair follicle planting, so that the transplanted hair is closer to the natural state of the original hair and improves the overall aesthetics.
[0031] The implantation effect evaluation module is based on a discrete elastic rod model. It simulates the growth effect of the current user's hair after implantation and evaluates the effect of the current implantation plan. The discrete elastic rod model regards the implanted hair as a structure composed of rigid segments connected by elastic connections. Each node has degrees of freedom, including position and direction. The elastic connection simulates the bending and torsional stiffness inside the hair to simulate the user's hair implantation effect and make an evaluation.
[0032] When simulating the dynamic behavior of hair, a dynamic equation is established, and the equation form is:
[0033] where F i is the resultant force acting on node i, k ij is the elastic coefficient matrix between nodes i and j, r i With r j is the position vector of nodes i and j, y iis the external force acting on i, i is the hair after implantation. After establishment, the established equation is solved by the iteration method. The evaluation of the implantation effect is based on the comparison between the simulation results and the user's expectations. The comparison includes the overall appearance, density, directional distribution and naturalness of the hair. By adjusting the parameters in the implantation plan, including the implantation density, angle and depth, and re-simulating, the implantation effect can be continuously optimized to achieve user satisfaction.
[0034] The discrete elastic rod model in the present application is a mathematical model for simulating and analyzing the movement and deformation of a slender elastic body in three-dimensional space. This model is approximated by discretizing a continuous elastic body into a series of rigid segments connected by joints or nodes. Each rigid segment can have certain physical properties of length, mass, and moment of inertia, while the nodes allow relative rotation and bending between adjacent segments. The modeling steps are: discretizing the continuous elastic rod into a series of rigid segments, determining the physical properties of the length, mass, and moment of inertia of each rigid segment, assigning degrees of freedom to each node, and determining its initial position and posture. According to the physical properties and deformation of the elastic rod, an elastic potential energy function is established. This function is usually related to the relative position and posture of the node, including bending energy and torsional energy. The Lagrange equation or the Newton-Euler equation method is used to derive the dynamic equation describing the node motion. The dynamic equation is solved by numerical methods to obtain the changes in the node position, velocity, and acceleration over time. According to the solution results, visualization and data analysis post-processing are performed to evaluate the motion and deformation characteristics of the elastic rod.
[0035] The history record storage module is used to store the data in the hair transplantation system and save the data based on cloud storage.
[0036] Reference Figure 2 As shown, the precise and traceless hair transplantation method with high survival rate, the transplantation steps are: S1. The doctor collects the user's hair data and uploads the collected data; S2, analyzing the collected data to determine the current head hair condition of the user; S3, uploading the judgment result to the personalized planting plan generation module, and recommending a suitable planting plan according to the specific hair condition of the user; S4. Evaluate the hair after implantation according to the current implantation plan, obtain the estimated result after implantation, and check whether it meets the user's needs. If it meets the user's needs, implantation is performed according to the current implantation plan. If it does not meet the user's needs, modify the implantation parameters in the implantation plan and continue the simulation until the user's needs are met; S5. Transplant the user's hair according to the established transplantation plan, and save the data parameters in the process to support subsequent decision-making.
[0037] By collecting the user's hair data and conducting a detailed analysis, we can accurately determine the user's hair condition and recommend the most suitable personalized implant plan for the user. This customized service can better meet the user's specific needs and improve the treatment effect. The personalized implant plan is based on the user's actual hair condition and needs, which can ensure that the implant process is more accurate and effective. By simulating and evaluating the estimated results after implantation, the implant parameters can be adjusted in time to ensure that the implant effect reaches the best state, thereby improving the treatment effect. Sufficient simulation and evaluation before implantation can predict and avoid possible risks and complications, which helps to reduce uncertainty during the operation, improve the safety of the operation, and reduce the risk to patients.
[0038] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.
Claims
1. The precise, traceless and high survival rate hair transplantation system is characterized by: The hair transplantation system includes: a hair data collection module, a hair analysis module, a personalized transplantation plan generation module, a history record storage module and a transplantation effect evaluation module; The hair data collection module is used to collect the user's hair data and upload the data to the hair analysis module; The hair analysis module is used to analyze the acquired hair data, determine the current head hair condition of the user, and upload the condition data to the personalized planting plan generation module; The personalized planting plan generation module is used to generate a planting plan suitable for the current user according to the head hair condition of the current user; The historical record storage module is used to store historical analysis data to make decisions for subsequent hair analysis and transplantation; The implantation effect evaluation module evaluates the survival status and implantation effect of the current user's hair after implantation based on the generated implantation plan.
2. The micro-traceless hair transplantation system with high survival rate according to claim 1, characterized in that: The data collected by the hair data acquisition module include hair follicle data and hair sparseness data, among which the hair coefficient data is collected based on images. The collection step is to aim the camera at the user's head to shoot the head, including the temples, forehead and top of the head, to obtain the user's head image data. The hair follicle data is collected based on manual acquisition. The user's current hair is cut off to obtain hair samples for analysis, and the obtained data is uploaded to the hair analysis module for analysis.
3. The micro-traceless hair transplantation system with high survival rate according to claim 1, characterized in that: The hair analysis module analyzes the areas where the user's hair is sparse in the acquired image data based on the image analysis module, and determines the estimated number of transplanted hair in the current area; the hair sample analysis includes the health status analysis and hair quality analysis of the hair follicles, and the hair samples are viewed based on professional instruments to generate a test report.
4. The micro-traceless hair transplantation system with high survival rate according to claim 3, characterized in that: The acquired image data is processed for clarity. After clarity, the image data is amplified by 50 times. The image is identified and distinguished between normal hair follicles and atrophic hair follicles based on edge detection, and the number of hairs per square centimeter is calculated. The calculation formula for the number of hairs per square centimeter is: Where A is the number of hairs per square centimeter, B is the hair data in the enlarged area of the image, and S is the area of the enlarged area of the current image; The analyzed user hair condition data is uploaded to the personalized planting plan generation module, and the planting plan is generated based on the user's current hair condition.
5. The micro-traceless hair transplantation system with high survival rate according to claim 1, characterized in that: The personalized implantation plan generation module classifies the user's hair based on the acquired data. The hair classification includes less hair volume, more hair volume and medium hair volume. The classification is based on the threshold value of the hair volume obtained from big data. The value of the current user analyzed by the hair analysis module is compared with the acquired threshold value to classify the hair situation of the current user. According to different classification results, a personalized implantation plan is generated for the user. Suppose the acquired threshold is C, and the threshold C is further divided into two endpoint values, C1 and C2. The acquired user hair volume data is D. The comparison form is: if D>C2, the current user's hair volume is classified as more hair volume. If D<C1, the current user's hair volume is classified as more hair volume. Continue to judge. If C1<D<C2, the current user's hair volume is classified as medium hair volume. Different implantation plans are given for users with different hair volume conditions; based on the implantation data stored in the historical record storage module, the currently selected implantation plan is optimized.
6. The micro-traceless hair transplantation system with high survival rate according to claim 5, characterized in that: According to the data analysis results, combined with the patient's hair loss situation and expected effect, the planting area is accurately divided and the planting density is adjusted to ensure that the hair is evenly and naturally distributed. The planting plan is optimized by evaluating the performance of different technologies in similar situations based on historical data to optimize the planting technology for users. For patients with a large hair loss area but sufficient hair follicle resources in the donor area, FUE technology is selected to reduce postoperative scars. For patients with a small hair loss area but poor hair follicle quality, microtransplantation technology is used. The natural growth direction and angle information of the hair in the data analysis results are used to optimize the hair follicle planting angle and direction in the planting plan to ensure that the transplanted hair appears natural and beautiful.
7. The micro-traceless hair transplantation system with high survival rate according to claim 1, characterized in that: The implantation effect evaluation module is based on a discrete elastic rod model. It simulates the growth effect of the current user's hair after implantation and evaluates the effect of the current implantation plan. The discrete elastic rod model regards the implanted hair as a structure composed of rigid segments connected by elastic connections. Each node has degrees of freedom, including position and direction. The elastic connection simulates the bending and torsional stiffness inside the hair to simulate the user's hair implantation effect and make an evaluation.
8. The micro-traceless hair transplantation system with high survival rate according to claim 7, characterized in that: When simulating the dynamic behavior of hair, a dynamic equation is established, and the equation form is: Among them, F i is the resultant force acting on node i, k ij is the elastic coefficient matrix between nodes i and j, r i With r j is the position vector of nodes i and j, y i is the external force acting on i, i is the hair after implantation. After establishment, the established equation is solved by the iteration method. The evaluation of the implantation effect is based on the comparison between the simulation results and the user's expectations. The comparison includes the overall appearance, density, directional distribution and naturalness of the hair. By adjusting the parameters in the implantation plan, including the implantation density, angle and depth, and re-simulating, the implantation effect can be continuously optimized to achieve user satisfaction.
9. The micro-traceless hair transplantation system with high survival rate according to claim 1, characterized in that: The history record storage module is used to store the data in the hair transplantation system and save the data based on cloud storage.
10. A fine, traceless and high survival rate hair transplantation method, characterized in that: The planting steps are: S1. The doctor collects the user's hair data and uploads the collected data; S2, analyzing the collected data to determine the current head hair condition of the user; S3, uploading the judgment result to the personalized planting plan generation module, and recommending a suitable planting plan according to the specific hair condition of the user; S4. Evaluate the hair after implantation according to the current implantation plan, obtain the estimated result after implantation, and check whether it meets the user's needs. If it meets the user's needs, implantation is performed according to the current implantation plan. If it does not meet the user's needs, modify the implantation parameters in the implantation plan and continue the simulation until the user's needs are met; S5. Transplant the user's hair according to the established transplantation plan, and save the data parameters in the process to support subsequent decision-making.