Method and system for generating AI-assisted plastic surgery plan and predicting postoperative effect

Abstract

The invention relates to a method and a system for generating an AI-assisted plastic surgery scheme and pre-judging a postoperative effect. The system includes a computer processor; the AI engine module comprises an AI model; a computer memory; the computer processor performs operations including: receiving user input data; processing the input data; generating a surgery plan and / or a predicted postoperative patient face visual model, and storing and displaying the surgery plan and / or the predicted postoperative patient face visual model; after the operation plan is performed on the face of the patient before the operation to form an actual postoperative face of the patient, receiving postoperative feedback including evaluating the predicted degree of closeness of the face of the postoperative patient to the actual face of the postoperative patient; and optimizing the AI model using post-operative feedback. The method is used for preoperative consultation and planning of facial cosmetic surgery, and aims to enhance the efficiency and effect of design and consultation of facial cosmetic surgery.

Description

Methods and systems for AI-assisted cosmetic surgery plan generation and postoperative effect prediction Technical Field

[0001] This invention relates to the fields of cosmetic surgery and artificial intelligence (hereinafter referred to as "AI"), and in particular to a method and system for generating AI-assisted cosmetic surgery plans and predicting postoperative effects. Background Technology

[0002] Facial cosmetic surgery encompasses a range of interventions, including rhinoplasty, blepharoplasty, facelift, ear augmentation, chin augmentation, lip augmentation, eyebrow lift, and injectable fillers. Each procedure requires precise planning to achieve optimal aesthetic and functional results.

[0003] Surgical markings serve as crucial blueprints, guiding surgeons to perform procedures with precision. Traditionally, these markings are hand-drawn, heavily reliant on the surgeon's expertise and judgment. However, hand-drawn markings are subjective and variable, potentially leading to asymmetry, inefficient procedures, and poor outcomes. Furthermore, they are time-consuming and lack repeatability, and may not always perfectly align with a patient's unique anatomy or desired aesthetics.

[0004] Injectable dermal fillers require precise placement to enhance facial contours, reduce wrinkles, or restore volume. Achieving the desired results while minimizing invasiveness necessitates accurate injection site selection, precise filler dosage, and understanding of key anatomical structures such as bones, blood vessels, and nerves. Using low-gauge needles increases the risk of complications, such as puncturing blood vessels or nerves, exacerbating these challenges. Variations in the skill level of the injector and differences in anatomical structures further complicate the process of achieving consistent results.

[0005] A significant challenge in facial cosmetic surgery lies in the consultation phase. Potential patients often hesitate due to uncertainty about the outcome, leading to prolonged consultations where doctors attempt to explain and visualize the potential results. Current methods, such as before-and-after photo comparisons, hand sketches, or static simulations, typically fail to capture the dynamic nature of personalized outcomes. This mismatch can result in dissatisfaction, hesitation, or unrealistic expectations, impacting patient confidence and surgical results.

[0006] Advances in AI, particularly in facial recognition and medical imaging, have demonstrated immense potential across various fields. Facial recognition systems utilize convolutional neural networks (CNNs) to analyze facial features, contours, symmetry, and proportions with high precision from images and videos. In the medical field, facial recognition algorithms have been used to diagnose syndromes, assess facial symmetry, and track changes in facial structure over time. However, most current systems excel at static facial analysis and lack the dynamic, real-time adaptability and responsiveness required for surgical and injection consultations. Furthermore, AI solutions tailored for beauty applications often fail to incorporate comprehensive datasets, such as demographic variations, medical imaging, and feedback loops, to ensure customization and reliability.

[0007] Integrating AI into medical procedures has shown significant promise across various fields, including diagnosis, treatment planning, and robotic surgery. However, its applications in surgical marking and dermal fillers, particularly in facial cosmetic surgery, remain largely unexplored. Currently, AI solutions for surgery are typically limited to image recognition or assisting with intraoperative decision-making, with little focus on preoperative planning tools that can aid in consultation or directly influence surgical precision. Summary of the Invention

[0008] One or more embodiments of the present invention relate to the application of AI in cosmetic surgery, such as facial cosmetic surgery. One or more embodiments of the present invention include apparatus, systems, and methods for predicting postoperative three-dimensional visualization during consultation, for generating precise surgical markers for cosmetic surgery, and for determining injection points, injection volumes, and injection trajectories for injectable fillers such as Botox (registered trademark) and hyaluronic acid.

[0009] One or more embodiments of the present invention provide methods and systems for generating AI-assisted cosmetic surgery plans and predicting postoperative effects, aiming to enhance the design and consultation of cosmetic surgeries (such as facial cosmetic surgeries). One or more embodiments can be used in clinical practice, such as during consultations and in medical training environments. One or more embodiments can be used to automatically apply markers or plans to a patient's face with minimal surgical intervention to assist clinical practice.

[0010] This invention discloses a computer system for generating AI-assisted cosmetic surgery plans and predicting postoperative effects, comprising: at least one computer processor; an input module; a visualization module; an AI engine module containing at least one AI model; and a computer memory storing instructions. When the at least one computer processor executes the instructions, the operations performed include: receiving input data input through the input module; processing the input data using the AI ​​engine module; generating a surgical plan using the AI ​​engine module; the surgical plan including surgical marking and / or injection procedures; and visualizing the results, including generating a visualization model using the AI ​​engine module; the visualization model comprising components generated by the AI ​​engine module. The system includes a block-predicted postoperative patient facial visualization model, or a preoperative patient facial visualization model and / or a preoperative patient facial visualization model with surgical markers superimposed on the preoperative patient face using an AI engine module; storing the surgical plan and / or visualization model in a computer memory; displaying the surgical plan and / or visualization model through a visualization module; storing the surgical plan in the computer memory after it is determined; and receiving postoperative feedback on the AI ​​engine module after performing the surgical plan on the patient's face and forming the actual postoperative patient face, and using the postoperative feedback to optimize at least one AI model; the postoperative feedback includes an assessment of the closeness between the predicted postoperative patient face and the actual postoperative patient face.

[0011] Specifically, the visualization model generated by the AI ​​engine module is based on the input data and / or the surgical plan generated by the AI ​​engine module.

[0012] Specifically, the surgical plan generated by the AI ​​engine module is based on the input data and / or the visualization model generated by the AI ​​engine module.

[0013] Furthermore, the at least one computer processor is configured to perform operations of reviewing, adjusting, and dynamically responding to the surgical plan before approval, including: adjusting or modifying input data and / or the visualization model generated by the AI ​​engine module through a user interface and / or in cooperation with the AI ​​engine module; reviewing and adjusting the surgical plan generated by the AI ​​engine module to achieve the expected results; regenerating the surgical plan and updating the visualization model in real time; and storing and displaying the corresponding surgical plan and visualization model.

[0014] Furthermore, the computer system allows for multi-user collaboration.

[0015] Specifically, the at least one computer processor is configured to, in performing the review, adjustment of surgical plan and dynamic feedback operations, include modifying the predicted postoperative patient facial parameters; and subsequently adjusting and regenerating the surgical plan.

[0016] Specifically, the input data includes preoperative patient facial input data acquired by the facial recognition system; the at least one computer processor is configured to perform the review, adjustment of surgical plan and dynamic feedback operations, including updating the preoperative patient facial input data, thereby adjusting and regenerating the surgical plan and updating the postoperative patient facial visualization model in real time.

[0017] Furthermore, the at least one computer processor is configured to, after the surgical plan is approved, use a marking device to perform actual physical marking on the patient's actual face according to the surgical plan.

[0018] Specifically, the at least one computer processor is configured to automatically implement surgical plans using the marking device to guide the marker pen or to mark the patient's actual face without user intervention.

[0019] Specifically, the input data includes preoperative facial input data of the patient obtained by the facial recognition system; wherein the AI ​​engine module processes the preoperative facial input data of the patient to determine a set of demographic data and / or medical history of the patient; the AI ​​engine module generates a surgical plan based on the demographic data and / or medical history.

[0020] Specifically, the postoperative feedback includes postoperative results programmed to be uploaded to the AI ​​engine module at specified postoperative time intervals.

[0021] This invention also discloses another computer system for generating AI-assisted cosmetic surgery plans and predicting postoperative results, comprising: at least one computer processor; an input module; a visualization module; an AI engine module containing at least one AI model; and a computer memory storing instructions. When the at least one computer processor executes the instructions, the operations it performs include: receiving input data input through the input module; processing the input data using the AI ​​engine module; visualizing the results, including generating a postoperative patient facial visualization model predicted by the AI ​​engine module; and displaying the predicted postoperative patient facial visualization model through the visualization module.

[0022] Specifically, the predicted postoperative patient facial visualization model is generated based on the input data and / or various factors, including, for example, previous surgical outcomes of similar populations and risk factors.

[0023] Furthermore, the at least one computer processor is configured to allow modification of the input data and the various factors, and to update the predicted postoperative patient facial visualization model based on the modifications.

[0024] This invention discloses a method for generating AI-assisted cosmetic surgery plans and predicting postoperative effects, comprising: a computer processor receiving input data through an input module; processing the input data using an AI engine module; generating a surgical plan using the AI ​​engine module; the surgical plan including surgical markings and / or injection protocols; visualizing the results, including generating a visualization model using the AI ​​engine module; the visualization model including a postoperative patient facial visualization model predicted by the AI ​​engine module, or further including a preoperative patient facial visualization model and / or a preoperative patient facial visualization model with surgical markings superimposed on the preoperative patient face using the AI ​​engine module; wherein, generating the surgical plan can be done before or after generating the visualization model; storing the surgical plan and / or visualization model in a computer memory; displaying the surgical plan and / or visualization model through a visualization module; storing the surgical plan in the computer memory after it is determined; and after performing the surgical plan on the patient's face and forming the actual postoperative patient face, receiving postoperative feedback on the AI ​​engine module and using the postoperative feedback to optimize at least one AI model; the postoperative feedback including assessing the closeness between the predicted postoperative patient face and the actual postoperative patient face.

[0025] Specifically, the visualization model generated by the AI ​​engine module is based on the input data and / or the surgical plan generated by the AI ​​engine module.

[0026] Specifically, the surgical plan generated by the AI ​​engine module is based on the input data and / or the visualization model generated by the AI ​​engine module.

[0027] Furthermore, prior to the approval of the surgical plan, the surgical plan can be reviewed, adjusted, and dynamic feedback can be provided, including adjusting or modifying the input data and / or the visualization model generated by the AI ​​engine module through the user interface and / or in conjunction with the AI ​​engine module, thereby reviewing and adjusting the surgical plan generated by the AI ​​engine module to achieve the expected results, regenerating the surgical plan and updating the visualization model in real time, and storing and displaying the corresponding surgical plan and visualization model.

[0028] The method allows for multi-user collaboration.

[0029] Specifically, the steps of reviewing, adjusting, and dynamically feeding back the surgical plan include modifying the predicted postoperative facial parameters of the patient; and then adjusting and regenerating the surgical plan.

[0030] Specifically, the input data includes preoperative facial input data of the patient obtained by the facial recognition system; the steps of reviewing, adjusting and dynamically feeding back the surgical plan include updating the preoperative facial input data of the patient, and then adjusting and regenerating the surgical plan and updating the postoperative facial visualization model of the patient in real time.

[0031] Furthermore, after the surgical plan is approved, it is sent to a marking device, which makes actual physical marks on the patient's face according to the surgical plan.

[0032] Specifically, without user intervention, the marking device guides the marker pen to automatically implement the surgical plan or marks the actual patient's face by directly projecting light or laser onto it.

[0033] Specifically, the input data includes preoperative facial input data of the patient obtained by the facial recognition system; the AI ​​engine module processes the preoperative facial input data to determine a set of demographic data and / or medical history of the patient; the AI ​​engine module generates a surgical plan based on the demographic data and / or medical history.

[0034] Specifically, the postoperative feedback includes postoperative results programmed to be uploaded to the AI ​​engine module at specified postoperative time intervals.

[0035] This invention also discloses another method for generating AI-assisted cosmetic surgery plans and predicting postoperative effects, comprising: a computer processor receiving input data input through an input module; processing the input data using the AI ​​engine module; visualizing the results, including generating a postoperative patient facial visualization model predicted by the AI ​​engine module using the AI ​​engine module; and displaying the predicted postoperative patient facial visualization model through a visualization module.

[0036] In at least one embodiment, a computer system is provided, comprising: at least one computer processor; an artificial intelligence (AI) engine module including at least one artificial intelligence (AI) model; and a computer memory storing instructions that, when the at least one computer processor executes the instructions, cause the at least one computer processor to perform the following operations: receiving input data input by a user to an input module; processing the input data using the AI ​​engine module; generating a surgical plan based on the input data using the AI ​​engine module; generating a postoperative patient facial visualization model as predicted by the AI ​​engine module based on the input data and the surgical plan generated by the AI ​​engine module; storing the postoperative patient facial visualization model in the computer memory; and displaying the postoperative patient facial visualization model through a visualization module.

[0037] In at least one embodiment, after the step of generating a postoperative patient facial visualization model, the at least one computer processor is configured to allow a user to modify the input data; and the at least one computer processor is configured to generate an improved postoperative patient facial visualization model in a computer memory based on the modification of the input data.

[0038] The at least one computer processor can be configured to allow the user to modify the surgical plan; and based on the user's modification of the surgical plan, to generate an improved postoperative patient facial visualization model in the computer memory.

[0039] Surgical protocols may include surgical markings.

[0040] The at least one computer processor can be configured to generate a visual model of the preoperative patient's face with surgical markers, which are generated by the AI ​​engine module and overlaid on the preoperative patient's face.

[0041] Modifications to the surgical plan by the user may include changes to surgical markers.

[0042] In at least one embodiment, a computer system is provided, comprising: at least one computer processor; an AI engine module containing at least one artificial intelligence model; and a computer memory storing instructions that, when executed by the at least one computer processor, cause the at least one computer processor to perform the following operations: receiving input data input by a user into an input module; processing the input data using the AI ​​engine module; generating a postoperative patient facial visualization model as predicted by the AI ​​engine module based on the input data; and displaying the postoperative patient facial visualization model via a visualization module.

[0043] The at least one computer processor can be configured to generate a visual alternative model of the postoperative patient's face based on the input data, as predicted by the AI ​​engine module, and to display the visual alternative model of the postoperative patient's face through the visualization module.

[0044] The at least one computer processor may be configured to generate multiple visual alternative models of the postoperative patient's face based on the input data, as predicted by the AI ​​engine module, and to display the multiple visual alternative models of the postoperative patient's face through a visualization module.

[0045] The AI ​​engine module can be configured to generate a surgical plan based on the input data and the postoperative patient facial visualization model.

[0046] In at least one embodiment, after the AI ​​engine module generates a postoperative patient facial visualization model, the at least one computer processor is configured to allow a user to modify the input data; and the at least one computer processor is configured to generate an improved postoperative patient facial visualization model based on the user's modification of the input data.

[0047] The at least one computer processor can be configured to allow modification of the surgical plan; and based on the modification of the surgical plan, generate an improved postoperative patient facial visualization model.

[0048] The at least one computer processor is configured to create a preoperative patient facial visualization model by using surgical markers, which are superimposed on the preoperative patient face created by the AI ​​engine module.

[0049] In at least one embodiment, a method is provided, comprising: receiving input data from a user into an input module via a computer processor; processing the input data using an AI engine module; generating a surgical plan based on the input data using the AI ​​engine module; generating a postoperative patient facial visualization model as predicted by the AI ​​engine module based on the input data and the surgical plan generated by the AI ​​engine module; storing the postoperative patient facial visualization model in a computer memory; and displaying the postoperative patient facial visualization model via a visualization module.

[0050] In at least one embodiment, after the step of generating a postoperative patient facial visualization model, the method may include: allowing a user to modify the input data; and, based on the modification of the input data, generating an improved postoperative patient facial visualization model in a computer memory.

[0051] The method may further include: allowing the user to modify the surgical plan; and generating an improved postoperative patient facial visualization model in a computer memory based on the user's modification of the surgical plan.

[0052] The surgical plan may include surgical markings.

[0053] The method may further include generating a preoperative facial visualization model of the patient with surgical markers, which are generated by overlaying the surgical markers onto the preoperative patient's face using an AI engine module.

[0054] The method may further include generating a preoperative facial visualization model of the patient with surgical markers, the surgical markers being overlaid on the preoperative patient's face using an AI engine module; the user's modification of the surgical plan includes modification of the surgical markers.

[0055] In at least one embodiment of the present invention, a method is provided, which may include: receiving input data input by a user into an input module on a computer processor; processing the input data using an AI engine module; generating a postoperative patient facial visualization model as predicted by the AI ​​engine module based on the input data; and displaying the postoperative patient facial visualization model through a visualization module.

[0056] The method may further include: generating a postoperative patient facial visualization candidate model based on the input data, as predicted by the AI ​​engine module, and displaying the postoperative patient facial visualization candidate model through a visualization module.

[0057] The method may further include: generating more visual candidate models of the postoperative patient's face based on the input data, as predicted by the AI ​​engine module; and displaying the multiple visual candidate models of the postoperative patient's face through a visualization module.

[0058] The AI ​​engine module can be configured to generate a surgical plan based on the input data and the postoperative patient facial visualization model.

[0059] In at least one embodiment, after the AI ​​engine module generates a postoperative patient facial visualization model, the method may include allowing a user to modify the input data; and, based on the user's modification of the input data, generating an improved postoperative patient facial visualization model through the visualization module.

[0060] The method may further include: allowing the user to modify the surgical plan; and generating an improved postoperative patient facial visualization model based on the modification of the surgical plan.

[0061] The method may also include creating a preoperative patient facial visualization model by using surgical markers, which are generated by overlaying the preoperative patient face created by the AI ​​engine module.

[0062] After the step of generating a visual model of the postoperative patient's face, the at least one computer processor can be configured to allow the user to modify the postoperative patient's face; wherein the at least one computer processor is configured to generate an improved surgical plan based on the modifications to the postoperative patient's face.

[0063] In at least one embodiment, after the AI ​​engine module generates a visual model of the postoperative patient's face, the at least one computer processor is configured to allow the user to modify the postoperative patient's face; wherein the at least one computer processor is configured to generate an improved surgical plan based on the modifications to the postoperative patient's face.

[0064] In at least one embodiment, after the step of generating a visual model of the postoperative patient's face, the method may include allowing a user to modify the postoperative patient's face; and generating an improved surgical plan based on the modifications to the postoperative patient's face.

[0065] After the AI ​​engine module generates a visual model of the postoperative patient's face, the method may include allowing the user to modify the postoperative patient's face; and generating an improved surgical plan based on the modifications to the postoperative patient's face.

[0066] In the technical solutions described and protected by this invention, all operations performed on objects such as "preoperative patient face", "postoperative patient face" and "patient face" are, unless otherwise specified, referring to the processing performed by the computer system on the corresponding model (including but not limited to, visualization models such as images and videos and / or numerical values) generated by it (such as generated by the AI ​​engine module) or input into the system as input data. The essence of such operations is the information processing process or method implemented by the computer (system or device).

[0067] This invention can be applied to preoperative consultation and planning, aiming to improve the efficiency and effectiveness of consultation and surgical plan design for cosmetic surgery (such as facial cosmetic surgery), thereby improving surgical precision and striving to greatly match patients' expectations of surgical results and improve patient satisfaction. Attached Figure Description

[0068] Figure 1 is a simplified block diagram of system components, methods, and / or apparatus according to at least one embodiment of the present invention; Figure 2A is a first part of a flowchart of a first method or process according to at least one embodiment of the present invention; Figure 2B is a second part of a flowchart of the first method; Figure 3 is a flowchart of a second method according to at least one embodiment of the present invention; Figure 4 is a flowchart of a third method according to at least one embodiment of the present invention. Detailed Implementation

[0069] Figure 1 is a simplified block diagram of system components, methods and / or apparatus according to at least one embodiment of the present invention.

[0070] The components in block diagram 1 include computer memory 2, visualization module 4, user computer processor 6, input module 8, artificial intelligence (hereinafter referred to as "AI") engine module 10, and optionally, server computer system 12 and tagging device 22. Server computer system 12 includes one or more server computer devices 14, each device including one or more server computer processors 16, one or more server computer memories 18, and one or more AI engine modules 20. Each AI engine module 20 may include one or more AI engine models 21, and each AI engine module 10 may include one or more AI engine models 11.

[0071] Computer memory 2 and server computer memory 18 can be any form of computer and / or electronic memory. Each visualization module 4, input module 8, AI engine module 10 and AI engine module 20 may include or may be computer software stored in computer memory 2 and / or server computer memory 18 and / or other computer memory, and executed by user computer processor 6 and / or server computer processor 16.

[0072] Input module 8 may be, or may include, for example, a computer, mobile phone or tablet touch screen, computer keyboard, 3D scanner, camera or other such image or video acquisition device, and / or computer mouse.

[0073] Figure 2A is the first part 100a of a flowchart of a first method or process according to at least one embodiment of the present invention.

[0074] In step 102, initial data input: The input data may include at least one of the following: patient data, including the type of surgery, media such as images or videos, medical images, patient information, demographic data and medical history, and the expected results. This data is input into the input module 8 so that it can be transmitted to the AI ​​engine modules 10 and / or 20 and executed by the computer processors 6 and / or 16 according to the computer program stored in the computer memory 2 and / or 18.

[0075] In step 104, a surgical plan is generated: the AI ​​engine module 10 is programmed to process the input data from step 102, as well as additional datasets, to analyze facial anatomy, proportions, symmetry, and other relevant indicators. Based on this analysis, computer software stored in the AI ​​engine module 10 and / or computer memory 2 is executed by the AI ​​engine module 10 and / or the user computer processor 6. The AI ​​engine module 10 generates a precise surgical marking, injection plan, or surgical plan tailored to the patient's anatomy and surgical goals.

[0076] In step 106, the results are visualized: computer software stored in the visualization module 4 and / or computer memory 2 is programmed and executed by the visualization module 4 and / or user computer processor 6 to generate a three-dimensional visualization model of the patient's face, the patient's face with superimposed surgical markings, injection protocols or surgical protocols, and / or the postoperative patient's face as predicted by the AI ​​engine module 10 and / or visualization module 4.

[0077] In at least one embodiment, step 106 may occur before step 104. In this embodiment, in step 106, the AI ​​engine module 10 is programmed to process the input data from step 102, as well as additional datasets, to analyze facial anatomy, proportions, symmetry, and other relevant indicators; based on this analysis, computer software stored in the visualization module 4 and / or computer memory 2 is programmed and executed by the visualization module 4 and / or user computer processor 6 to generate a three-dimensional visualization model of the patient's face, and / or the postoperative patient's face as predicted by the AI ​​engine module 10 and / or visualization module 4.

[0078] Subsequently, in step 104, the AI ​​engine module 10 is programmed to process the input data from step 102, the patient facial data predicted in step 106, and additional relevant datasets. Based on this analysis, computer software stored in the AI ​​engine module 10 and / or computer memory 2 is executed by the AI ​​engine module 10 and / or the user computer processor 6. The AI ​​engine module 10 generates precise surgical markings, injection protocols, or surgical plans tailored to the patient's anatomy and surgical goals to achieve the results displayed on the predicted patient face in step 106.

[0079] In step 108, the solution is reviewed and modified. The user can review the results provided by visualization module 4 in step 106; visualization module 4 may include a display, such as a computer monitor, and / or a tablet or mobile phone display.

[0080] Input module 8 and / or computer software for input module 8 are configured to allow users to change the input data and surgical markers, injection protocols or surgical protocols in real time via input module 8, and the results of the changes are configured to be dynamically regenerated and displayed via visualization module 4.

[0081] Alternatively, one or more embodiments of the present invention allow users to make changes to the desired outcome of the postoperative patient's facial display in real time, and surgical markers, injection protocols, or surgical protocols are configured to be dynamically regenerated and displayed by the visualization module 4 according to the changes in the desired outcome.

[0082] As shown in step 110, if the user makes changes to the plan or expected result, the program will return to step 106.

[0083] If the user intends to finalize the solution, the next step in the process is node A, which points to step 112 in part of flowchart 100b, as shown in Figure 2B.

[0084] In step 112, the user can finalize the plan by approving surgical markers, injection protocols, or surgical protocols, for example, by inputting information into the input module 8 by the user according to computer software stored in, for example, the input module 8 and / or the computer memory 2.

[0085] In step 114, optionally, the input module 8 and / or computer memory 2 are programmed with computer software to allow the user to upload postoperative results at predetermined time intervals, such as by uploading facial images and / or videos of the patient immediately after surgery, one week after surgery, and one to three months after surgery. Optionally, the input module 8 and / or computer memory 2 are programmed to allow the user to assess how close these results are to the predictions generated by the AI ​​model provided by the AI ​​engine module 10, and to provide additional feedback to the AI ​​engine module 10 via the input module 8. The AI ​​engine module 10 can be programmed with computer software to further optimize the model using this feedback.

[0086] Figure 3 is a flowchart 200 of a second method or process according to at least one embodiment of the present invention.

[0087] In step 202, initial data input: The input data may include at least one of the following: patient data, including surgery type, media such as images or videos, medical images, patient information, demographic data and medical history, and expected results; this input data is executed by the user computer processor 6 using a computer program stored in the computer memory 2, and input to the AI ​​engine module 10 using the input module 8. In at least one embodiment, the AI ​​engine module 10 and / or the input module 8 are further programmed by computer software to receive additional information input, including manually generated surgical markings, injection protocols, or surgical plans.

[0088] In step 204, the procedure is reviewed: the AI ​​engine module 10 is programmed to process the data provided in step 202, as well as the user's manual markings, injection plans, or surgical plans, to analyze facial anatomy, proportions, symmetry, and other relevant indicators. Based on these inputs and the analysis of the AI ​​engine module 10, the AI ​​engine module 10, programmed by computer software, generates recommended modifications to the manual markings or surgical plans.

[0089] In step 206, the results are visualized: a 3D visualization model of the patient's face, overlaid with the 3D visualization model of the patient's face based on the surgical markings, injection plan, or surgical plan input by the user through input module 8, and / or the 3D visualization model of the patient's face predicted based on the surgical markings, injection plan, or surgical plan input by the user, is generated by the AI ​​engine module 10 according to a computer program and displayed to the user through visualization module 4. Furthermore, overlaid with the surgical markings, injection plan, or surgical plan determined by the AI ​​engine module 10 according to a computer program, and the recommended modified patient's face, as well as the post-operative patient's face predicted by the recommended modifications generated by the AI ​​engine module 10, is displayed to the user through visualization module 4 according to computer programming.

[0090] In step 208, the solution is reviewed and modified. Users can review the results provided by visualization module 4 in step 206. Visualization module 4 may include a computer monitor.

[0091] Input data provided by the user through input module 8, and surgical markings, injection plans, or surgical plan modifications provided by AI engine module 10, including acceptance, alteration, or rejection of AI-recommended modifications, are configured to be performed in real time in at least one embodiment, and the results of the modifications are configured to be dynamically displayed using visualization module 4.

[0092] In at least one embodiment, computer software is provided, such as for AI engine module 10 and / or user computer processor 6, which allows the user to modify surgical markings, injection protocols, or surgical protocols using input module 8 to change the prediction result, or to modify the prediction result using input module 8 to change the surgical markings, injection protocols, or surgical protocols.

[0093] As shown in step 210, if the user modifies the solution, the program will return to step 206.

[0094] If the user intends to finalize the solution in step 210, the next step of the procedure proceeds to step 212 as shown in Figure 3.

[0095] In at least one embodiment, in step 212, the user can finalize the plan by providing input data to the input module 8 to approve surgical markers, injection protocols, or surgical protocols. The approved instructions are then processed by the user's computer processor 6 and stored in the computer memory 2 and / or displayed on the computer display of the visualization module 4.

[0096] Figure 4 shows a flowchart 300 of a third method or process according to at least one embodiment of the present invention.

[0097] In step 302, the input data may include at least one of the following: patient data, including the type of surgery, media such as images or videos, medical images, patient information, demographic data and medical history, and the expected results. This data is input into the input module 8 so that it can be implemented by the user computer processor 6 according to the computer programming stored in the computer memory 2 and transmitted to the AI ​​engine module 10.

[0098] In step 304, the AI ​​engine module 10 is programmed to process the input data from step 302, along with additional datasets, to analyze facial anatomy, proportions, symmetry, and other relevant indicators. Based on this analysis, at least two different versions of the postoperative patient's facial 3D visualization model are generated according to the patient's desired outcome, as predicted by the AI ​​engine module 10, and these at least two versions are displayed to the user. The AI ​​engine module 10 can provide several alternative visualization models of the postoperative patient's face based on factors including, but not limited to, the model training from previous surgeries, the user's desired outcome, and the feasibility and risk factors of surgeries based in part on the input data.

[0099] In step 306, the user computer processor 6 and / or AI engine module 10 and / or 20 are programmed to allow the user to select one of the postoperative patient facial visualization model versions to continue the procedure; the selected version is typically the one that best matches the patient's expectations, taking into account outcomes, risk factors, feasibility, recovery time, and any other such factors.

[0100] In step 308, AI engine modules 10 and / or 20 are programmed to process the input data provided in step 302, along with additional datasets, to analyze facial anatomy, proportions, symmetry, other relevant indicators, and the version selected in step 306, to generate precise surgical markings, injection protocols, or surgical plans to achieve the results displayed in the selected version. Optionally, surgical markings, injection protocols, or surgical plans can be generated for each displayed version of the postoperative patient's face before the user selects one of the versions in step 304. In step 308, AI engine modules 10 and / or 20 are programmed to generate surgical plans and store these plans in computer memory, such as memory 2, and / or display them on visualization module 4. AI engine modules 10 and / or 20 are programmed to generate these surgical plans based on and / or specifically tailored to the input data and the result version selected by the user through input module 8.

[0101] In step 310, optionally, AI engine modules 10 and / or 20 generate, according to programming, three-dimensional visualization models of the patient's face, overlaid with surgical markings, injection protocols, or surgical protocols, and / or the postoperative patient's face, and store them in computer memory 2 and / or display them on visualization module 4. These three-dimensional visualization models are predicted and generated by AI engine modules 10 and / or 20 according to programming based on surgical markings, injection protocols, or surgical protocols, and are stored in computer memory 2 and / or displayed to the user by visualization module 4.

[0102] Optionally, the process may flow from step 310 to node B, which in turn flows to step 108 on the partial flowchart 100a shown in Figure 2A.

[0103] In contrast, in step 312, one or more computer processors 6 and / or AI engine modules 10 and / or 20 are programmed to allow the user to finalize the treatment plan by approving surgical markers, injection protocols, or surgical protocols, for example, by user input to input module 8, which, according to computer software, is stored, for example, in input module 8, computer memory 2, and / or AI engine modules 10 and / or 20.

[0104] One or more embodiments of the present invention include a process executed by one or more computer processors and / or AI engine modules 10 and / or 20, comprising the following steps: (1) Patient data acquisition: Input data is input via input module 8, which may include at least one of the following: required procedures and patient-specific data, such as 3D facial scans, media such as photographs or videos, medical images (e.g., CT scans, MRI, X-rays, ultrasound, etc.), demographic data (age, sex, race, etc.), medical history including previous surgeries, allergies, medication use, and other relevant factors such as risk factors, recovery time preferences, height, weight, body fat percentage, and the patient's desired outcome. The desired outcome may be input as the specific amount of tissue to be removed at a specific point, the length measurement or degree of repositioning between two points, the volume or mass to be added or subtracted at a specific location, or a description of the desired final result, such as facial symmetry or wrinkle reduction. For example, in upper eyelid surgery, the input may include the patient's desire to remove excess skin and fat from the upper eyelid. This can be input as a numerical value, such as the area or volume of skin or fat to be removed from a specific region, or the overall desired outcome of the surgery, such as removing double eyelids or achieving symmetry between the eyes. The input data can be preprocessed by standardizing the collected data and ensuring consistent formatting. Image processing techniques can be used to enhance, segment, and extract key elements from the input medium, such as images or videos.

[0105] (2) Integration of various AI models: For example, through one or more AI engine modules 10 and / or 20, analyze patient-specific data, such as the patient's facial anatomy (including the distribution of skin, muscle and fat), assessment of key indicators (such as facial proportions, symmetry and skin elasticity), and expected results. Other information that needs to be analyzed may include datasets such as facial recognition of other members in the patient's demographic data, surgical protocols (such as surgical marking and injection protocols), previous surgical outcomes, relevant anatomical models (such as bone, blood vessel and nerve mapping), and default outcome criteria based on the selected surgery.

[0106] (3) Automatic generation of surgical plans based on computer programming: For example, through AI engine modules 10 and / or 20, such as precise surgical marking, injection protocols, or customized surgical plans based on the patient's unique facial anatomy and desired outcomes. AI engine modules 10 and / or 20 can generate multiple alternative plans, which are stored in computer memory 2 and displayed on visualization module 4 for the user to consider based on risk factors, feasibility, recovery time, and expected outcomes. For example, the patient's medical images can be used as part of the input data that AI engine module 10 may consider when generating surgical plans, adjusting injection location, angle, depth, and needle specifications to avoid damaging key anatomical features such as bone structures, blood vessels, or nerves, and generating alternative plans based on the user's risk tolerance or recovery time.

[0107] (4) Generate a three-dimensional visualization model of the patient's face, and / or overlay a patient facial visualization model based on surgical protocols such as surgical markings and / or injection protocols, and a postoperative patient facial visualization model predicted based on surgical protocols such as surgical markings and / or injection protocols, for example, through visualization module 4, programmed by computer software, executed by one or more computer processors 6, AI engine modules 10 and / or 20. In at least one embodiment, multiple versions of the postoperative patient facial visualization model may be generated, based on partial training of AI engine 10 and / or 20 on previous procedures, risk factors, feasibility, recovery time, patient-desired outcomes, and any other such factors. In at least one embodiment, the visualization model of step (4) may be generated prior to the surgical protocol.

[0108] (5) A user interface (UI), such as including an input module 8 and / or a visualization module 4, allows the user to review, adjust, and approve AI-generated surgical plans, such as surgical marking or injection plans, and / or integrate them with AI engine modules 10 and / or 20 according to computer software programming. In at least one embodiment, the user can adjust input data or modify surgical plans, such as surgical marking and / or injection plans, through the input module 8 according to software programming in the computer processor 6 and / or AI engine modules 10 and / or 20 to achieve the desired result. In at least one embodiment, based on risk factors, desired results, or other such factors, the user can view and adjust alternative plans generated by AI engine modules 10 and / or 20, and display them on the visualization module 4, and / or store them in the computer memory 2.

[0109] (6) In at least one embodiment, a dynamic feedback function is provided, for example, based on user changes, the actual results can be regenerated in real time in the visualization module 4 and / or in computer memory, such as computer memory 2, via the input module 8, visualization module 4, and AI engine modules 10 and / or 20. When the user modifies the input data or surgical plan via the visualization module 4 and / or in computer memory 2, the system (including one or more AI engine modules 10 and / or 20) is programmed to recalculate and update the visualization model in real time in computer memory 2 and display it on the visualization module 4 to reflect the new parameters, ensuring that the surgical plan remains accurate and adaptable, and providing immediate feedback on the changed input data.

[0110] (7) Once satisfied, the surgical plan is finalized and stored in the system's computer memory, such as computer memory 2.

[0111] (8) Optionally, the system can scan the user's surgical plan via photo or video, such as manual surgical marking, and analyze the input data via input module 8, such as via AI engine module 10 and / or 20, to provide a visual model of the predicted results, such as via visualization module 4, and propose improvement suggestions for the surgical plan (such as surgical marking), which are stored in computer memory 2. Alternatively, the user can use input module 8 to input a surgical plan, such as an injection plan, including location, depth, and volume, via a user interface, photo, or video. The system analyzes the input data, provides a visual model of the results via visualization module 4, and proposes improvement suggestions for the surgical plan (such as an injection plan) via AI engine module 10 and / or 20.

[0112] (9) Optionally, in at least one embodiment, any one of the input module 8, computer processor 6, and AI engine module 10 or 20 can be programmed by computer software to allow the postoperative results to be uploaded to the AI ​​engine module 10 or 20 at defined time intervals, such as immediately after surgery, one week after surgery, and three months after surgery, via the input module 8, to further optimize the AI ​​model of the AI ​​engine modules 10 and / or 20. In at least one embodiment, the AI ​​engine module 10 or 20 is programmed to record the results, storing them in the form of photos, videos, 3D facial scans, medical images, or numerical values ​​in the computer memory 2. In at least one embodiment, the user can evaluate the consistency between the results and the predictions generated by the model through the programming of the AI ​​engine modules 10 and / or 20 and / or by using the input module 8, provide specific feedback on any deviations, and record force majeure factors that may affect the results in the computer memory 2.

[0113] (10) Optionally, in step (5) or (6), the computer processor 6 and / or AI engine module 10 and / or 20 may be programmed by computer software to allow the user to adjust the AI-generated result of the postoperative patient face provided by the AI ​​engine module 10 via the input module 8, so as to regenerate a patient face image overlaid with a surgical plan, such as surgical markings or injection protocols, on the visualization module 4 according to the programming of the computer processor 6 and / or AI engine module 10 and / or 20. Adjustments may be made by interacting with the input module 8 to change values ​​related to various surgical actions and areas, or visually, via the visualization module 4, such as using a mouse on a computer or using a finger on a tablet, by selecting actions, clicking and dragging facial areas or sliders. In at least one embodiment, the surgical plan is dynamically updated in real time in the computer memory 2 based on the user's modifications to the postoperative patient face generation result (in at least one embodiment, these modifications are stored in the computer memory 2). In at least one embodiment, any changes made by a user to the surgical plan or the postoperative patient's face, and the resulting changes to the postoperative patient's face or surgical plan generated by the AI ​​engine module 10, can be stored, for example, in computer memory 2, for recall and visualization, such as for side-by-side comparison.

[0114] (11) Optionally, the system may allow multi-user collaboration, for example, between patients and doctors, multiple users can jointly generate, review and modify certain parts of the system.

[0115] (12) Optionally, in at least one embodiment, the marking device 22 is configured to mark or draw a surgical plan, such as a surgical marker or injection plan, on the patient's real face based on a surgical plan generated by the AI ​​engine 10 and / or 20. The marking device 22 may be a robotic arm or similar device that can be software-programmed according to the user's computer processor 6 and / or AI engine module 10 and / or 20, for example, to automatically implement the surgical plan without user or surgeon intervention by guiding the use of a marker. Alternatively, the marking device 22 may be configured to mark by directly projecting light or laser onto the patient's real face. After the surgical plan is generated, this marking device 22 can be applied to any point during the surgical procedure.

[0116] One or more embodiments of the present invention may use one or more computer software modules or components, which are stored in computer memory and executed by a computer processor. The one or more computer software modules may include (a) AI engine modules 10 and / or 20, (b) input module 8, and (c) visualization module 4.

[0117] (a) The AI ​​engine modules 10 and / or 20, in at least one embodiment, are programmed by computer software to: (i) generate surgical plans in part based on user input information using various types of AI models.

[0118] (ii) Use facial recognition models to identify, compare and extract relevant biometric data, such as size and patient details.

[0119] (iii) Generative AI models are used to generate realistic 3D models of patient faces in real time. Generative AI models can obtain information from AI and facial recognition models to generate 3D visualization models of the patient's face before surgery, the patient's face before surgery with surgical or injection plans superimposed, and the predicted patient's face after surgery.

[0120] (iv) AI models, facial recognition systems, and generative AI models are used in combination to accurately acquire input data, including patient data, predict optimal surgical markings, injection protocols, and other surgical procedures and outcomes, and generate various realistic patient facial models. Other datasets, such as anatomical models, best practices, and previous patient outcomes, can be used in conjunction with the input data or as part of the AI ​​model training. Furthermore, the system allows for real-time visualization of predictions in response to user modifications to input values, surgeries, injections, or surgical protocols, as well as the user's desired outcomes. The models used can include neural networks, such as convolutional neural networks; machine learning, such as supervised learning, unsupervised learning, and deep learning; decision trees; generative AI; regression models; classifier models; and / or other such models, algorithms, and training techniques. Models can be trained on layers of a comprehensive dataset, including anatomical models, previous surgical and filling protocols and outcomes (including media, such as images or videos of patients at various time intervals before and after surgery), surgical markings, injection protocols, and other surgical protocols, expectations and satisfaction with outcomes, genetic information, demographic information, and various other medically relevant information. Models can be used independently, sequentially in series with other models, or in parallel.

[0121] (v) Optionally, one or more models of the AI ​​engine module 10 may be stored and trained on a server computing system 12, which is communicatively connected to the user computer processor 6. The server computing system 12 may include one or more server computing devices 14, each of which may contain a server computer processor 16, a server computer memory 18, and the AI ​​engine module 20. The server computing system 12 may receive information from the user computer processor 6 via, for example, an input module 8, to run the model, and may communicatively connect its output to the user computer processor 6. In this way, necessary computing power can be transferred from the user computer processor 6 to the server computing system 12.

[0122] (b) Input module 8, in at least one embodiment, is programmed by computer software to: (i) accept the desired surgical procedure and input data, said input data including patient data, including 3D facial scans, photographs, videos, medical images (e.g., CT scans, MRI, X-rays, etc.), demographic data (age, sex, race, etc.), medical history, and other relevant factors such as height, weight, body fat percentage, and the patient's desired outcome. The desired outcome may be input as the amount of tissue removed at a specific point, the length dimension between two points or the degree of repositioning, the increase or decrease in volume or mass at a specific location, or a description of the desired final result.

[0123] (ii) It has the ability to integrate real-time data input, such as video scanning during consultations.

[0124] (c) Visualization module 4, in at least one embodiment, is programmed by computer software to: (i) provide a detailed, real-time 3D visualization model of the patient's face, overlaid with surgical markings and / or injection or surgical protocols generated by AI engine module 10, and postoperative patient face as predicted by AI engine module 10.

[0125] (ii) Optionally, additional information, such as key anatomical features, like skeletal structures, blood vessels, and nerves, may be overlaid to guide safe execution and achieve the desired results.

[0126] (iii) Allows real-time visualization of any changes to input or modifications to suggested surgical markers, and / or injection protocols, surgical procedures, and the user’s desired results.

[0127] Example of a use case for blepharoplasty: Users can input data via input module 8, including their specific patient data and demographic data related to upper blepharoplasty, indicating their desire to remove a certain amount of excess skin from the upper eyelid. Hidden features such as eyelid skin folds are an important part of upper blepharoplasty and may require manipulation of the eyelid to provide a better field of view during imaging or video acquisition, thus providing the AI ​​system with sufficient information for complete analysis.

[0128] For example, the system, through the AI ​​engine module 10, is programmed and / or configured by computer software to analyze patients' facial images and videos, recording various detection dimensions and standards for different areas of the eyes and surrounding regions. This includes identifying and considering ptosis, symmetry or asymmetry between the eyelids and eyebrows, the amount and thickness of excess skin, inflammation, skin lesions, and various other conditions. In Asian populations, demographic-specific features such as upper eyelid creases may also be identified. Default values ​​may initially be used to generate surgical markers and postoperative facial images. For example, the ratio of the distance between the tarsal plate and the upper eyelid crease and eyebrow should be 1:1.618, the golden ratio, and for Caucasians, the corneal reflection-eyelid margin distance should be between 3.5 and 4 mm, and symmetrical. These default dimensions may be overridden and rewritten by advanced users such as surgeons during data input.

[0129] The patient's interactive facial model (here, "interactive model" means "visual model," with "interactive" emphasizing the ability to allow users to modify and regenerate the visual model based on their modifications), the patient's interactive facial model overlaid with surgical markers, and the postoperative patient's interactive facial model predicted based on the surgical markers are generated by the AI ​​engine module 10 through computer programming. In at least one embodiment, the input module 8 is programmed to allow users to change values ​​associated with the surgical plan or each individual surgical marker, and the AI ​​engine module 10 is programmed and / or configured to regenerate the surgical markers and expected results in real time and display them through the visualization module 4. Alternatively, the user can interactively operate the input module 8 and / or the visualization module 4, and the surgical markers, values, and expected results will be regenerated in real time.

[0130] Alternatively, AI engine module 10 can generate one or more visual models of the patient's face after surgery based on various factors, such as previous surgical outcomes in similar populations, risk factors, etc. For example, AI engine module 10 can identify that the patient is Asian and has ptosis (drooping eyelid) and generate a visual version that corrects this problem without the patient specifically mentioning the condition or inputting corrections when entering the desired outcome. The surgical plan can be generated before or after the visual model is generated.

[0131] Once the user is satisfied with the surgical markings and results, the plan is finalized, and the finalized plan is configured to be stored in computer memory (e.g., computer memory 2). The surgical plan can be sent to marking device 22, which can be used to mark or draw on the patient's real face according to the plan generated by the AI ​​engine. Marking device 22 can be a robotic arm or similar device that can, for example, automatically implement the surgical plan by guiding a marker pen without user or surgeon intervention. Alternatively, marking device 22 can mark by directly projecting light or laser onto the patient's real face.

[0132] Post-operatively, other information may be uploaded, such as images and videos of the patient during a specified post-operative period. In at least one embodiment, the system and / or input module 8 is programmed to allow the user to evaluate the AI ​​results generated by the AI ​​engine module 10, compare them with actual results, and provide feedback on patient- and surgery-specific factors that occurred during surgery and recovery. This information can be added to the AI ​​engine module 10 and / or computer memory 2 for further optimization in future use.

[0133] In at least one embodiment, the AI ​​engine module 10 is programmed by computer software to continuously scan the patient's face via video to dynamically optimize the input data in response to additional information collected from the patient, such as changes in posture, facial expressions, or physical actions like raising the eyelids during user interaction with the system. This functionality allows for real-time updates to suggested surgical markings or injection protocols and visualizations of expected outcomes, improving accuracy and usability. Furthermore, the AI ​​model generated by the AI ​​engine module 10 is programmed by computer software to reflect the patient's face in real time, displaying posture, facial expressions, or facial positioning based on changes in the patient's movement. This real-time usability ensures the system remains responsive to surgeon- or patient-driven modifications, creating a seamless, interactive surgical experience.

[0134] In at least one embodiment, the procedure is not limited to facial cosmetic surgery. These procedures can facilitate a variety of surgical procedures, such as orthopedic or general surgery. For any such procedure, the face or facial aesthetic is replaced with a corresponding anatomical region, referencing a specific anatomical area; for example, for knee replacement surgery, it can be replaced with the knee joint; for breast augmentation surgery, it can be replaced with the breast; and for neurosurgery, it can be replaced with the head.

[0135] In this invention, any acquisition or collection of patient personal data, such as obtaining patient facial information through a facial recognition system, is legal, compliant, and strictly adheres to the relevant provisions of laws and regulations, including the Personal Information Protection Law of the People's Republic of China.

[0136] Although the invention has been described with reference to specific embodiments, many changes and modifications to the invention will be apparent to those skilled in the art without departing from the spirit and scope of the invention. Therefore, this patent is intended to include all such changes and modifications that are reasonably and appropriately included within the scope of the invention's contribution to the technical field.

Claims

1. A computer system, comprising: At least one computer processor; one input module; A visualization module; an AI engine module containing at least one AI model; a computer memory storing instructions; when the at least one computer processor executes the instructions, the operations performed include: receiving input data input through an input module; processing the input data using the AI ​​engine module; generating a surgical plan using the AI ​​engine module; the surgical plan including surgical marking and / or injection procedures; visualizing the results, including generating a visualization model using the AI ​​engine module; the visualization model including a postoperative patient face visualization model predicted by the AI ​​engine module, or further including a preoperative patient face visualization model and / or a preoperative patient face visualization model having surgical markings superimposed on the preoperative patient face using the AI ​​engine module; storing the surgical plan and / or visualization model in the computer memory; displaying the surgical plan and / or visualization model through the visualization module; and after performing the surgical plan on the patient's face and forming the actual postoperative patient face, receiving postoperative feedback on the AI ​​engine module, and optimizing at least one AI model using the postoperative feedback; the postoperative feedback including assessing the closeness between the predicted postoperative patient face and the actual postoperative patient face.

2. The computer system as claimed in claim 1, wherein: The visualization model generated by the AI ​​engine module is based on the input data and / or the surgical plan generated by the AI ​​engine module.

3. The computer system as described in claim 1, wherein: The surgical plan generated by the AI ​​engine module is based on the input data and / or the visualization model generated by the AI ​​engine module.

4. The computer system as claimed in claim 1, wherein: The at least one computer processor is configured to perform operations of reviewing and adjusting surgical plans and providing dynamic feedback, including: adjusting or modifying input data and / or the visualization model generated by the AI ​​engine module through a user interface and / or in cooperation with the AI ​​engine module, thereby reviewing and adjusting the surgical plan generated by the AI ​​engine module to achieve the expected results, regenerating the surgical plan and updating the visualization model in real time, and storing and displaying the corresponding surgical plan and visualization model.

5. The computer system as described in claim 4, which allows for multi-user collaboration.

6. The computer system as claimed in claim 4, wherein: The at least one computer processor is configured to, in performing the review, adjustment of surgical plan and dynamic feedback operations, include modifying the predicted postoperative patient facial parameters; and subsequently adjusting and regenerating the surgical plan.

7. The computer system as claimed in claim 4, wherein: The input data includes preoperative patient facial input data acquired by the facial recognition system; the at least one computer processor is configured to perform the review, adjustment of surgical plan and dynamic feedback operations, including updating the preoperative patient facial input data, thereby adjusting and regenerating the surgical plan and updating the postoperative patient facial visualization model in real time.

8. The computer system as claimed in claim 1, wherein: The at least one computer processor is configured to use a marking device to make actual physical markings on the patient's real face according to the surgical plan.

9. The computer system of claim 8, wherein: The at least one computer processor is configured to automatically implement surgical plans using the marking device to guide the marker pen or to mark the patient’s real face without user intervention.

10. The computer system of claim 1, wherein: The input data includes preoperative facial input data of the patient obtained by the facial recognition system; wherein the AI ​​engine module processes the preoperative facial input data of the patient to determine a set of demographic data and / or medical history of the patient; the AI ​​engine module generates a surgical plan based on the demographic data and / or medical history.

11. The computer system of claim 1, wherein: The postoperative feedback includes postoperative results programmed to be uploaded to the AI ​​engine module at specified postoperative time intervals.

12. A computer system, comprising: At least one computer processor; one input module; A visualization module; an AI engine module containing at least one AI model; a computer memory storing instructions; and operations performed by the at least one computer processor when executing the instructions, including: receiving input data input through an input module; processing the input data using the AI ​​engine module; visualizing the results, including generating a postoperative patient facial visualization model predicted by the AI ​​engine module based on the input data and / or various factors; and displaying the predicted postoperative patient facial visualization model through the visualization module.

13. The computer system of claim 12, wherein: The various factors mentioned include previous surgical outcomes and risk factors in similar populations.

14. The computer system of claim 13, wherein the at least one computer processor is configured to allow modification of the input data and the various factors, and to update the predicted postoperative patient facial visualization model based on the modification.

15. A method comprising: The computer processor receives input data through the input module; The input data is processed using the AI ​​engine module; Use the AI ​​engine module to generate surgical plans; The surgical plan includes surgical marking and / or injection protocol; result visualization includes generating a visualization model using an AI engine module; the visualization model includes a postoperative patient facial visualization model predicted by the AI ​​engine module, or also includes a preoperative patient facial visualization model and / or a preoperative patient facial visualization model with surgical markings superimposed on the preoperative patient's face using the AI ​​engine module; wherein, generating the surgical plan can be done before or after generating the visualization model; the surgical plan and / or visualization model are stored in computer memory; The surgical plan and / or visualization model are displayed through a visualization module; and after the surgical plan is performed on the patient's face and the actual postoperative patient face is formed, postoperative feedback is received on the AI ​​engine module and at least one AI model is optimized using the postoperative feedback; the postoperative feedback includes an assessment of the degree of similarity between the predicted postoperative patient face and the actual postoperative patient face.

16. The method of claim 15, wherein: The visualization model generated by the AI ​​engine module is based on the input data and / or the surgical plan generated by the AI ​​engine module.

17. The method of claim 15, wherein: The surgical plan generated by the AI ​​engine module is based on the input data and / or the visualization model generated by the AI ​​engine module.

18. The method of claim 15, wherein: Before the surgical plan is approved, it allows for review and adjustment of the surgical plan and provides dynamic feedback, including adjusting or modifying the input data and / or the visualization model generated by the AI ​​engine module through the user interface and / or in conjunction with the AI ​​engine module, thereby reviewing and adjusting the surgical plan generated by the AI ​​engine module to achieve the expected results, regenerating the surgical plan and updating the visualization model in real time, and storing and displaying the corresponding surgical plan and visualization model.

19. The method of claim 18, which allows for multi-user collaboration.

20. The method of claim 18, wherein: The steps of reviewing, adjusting, and dynamically feeding back the surgical plan include modifying the predicted postoperative facial parameters of the patient; and then adjusting and regenerating the surgical plan.

21. The method of claim 18, wherein: The input data includes preoperative facial input data of the patient obtained by the facial recognition system; the steps of reviewing, adjusting and dynamically feeding back the surgical plan include updating the preoperative facial input data of the patient, and then adjusting and regenerating the surgical plan and updating the postoperative facial visualization model of the patient in real time.

22. The method of claim 15, further comprising: Once the surgical plan is approved, it is sent to a marking device, which makes actual physical marks on the patient's face according to the surgical plan.

23. The method of claim 22, wherein: Without user intervention, the marking device guides the marker pen to automatically implement the surgical plan or marks the actual patient's face by directly projecting light or laser onto it.

24. The method of claim 15, wherein: The input data includes preoperative facial input data of the patient obtained by the facial recognition system; the AI ​​engine module processes the preoperative facial input data of the patient to determine a set of demographic data and / or medical history of the patient; the AI ​​engine module generates a surgical plan based on the demographic data and / or medical history.

25. The method of claim 15, wherein: The postoperative feedback includes postoperative results programmed to be uploaded to the AI ​​engine module at specified postoperative time intervals.

26. A method comprising: The computer processor receives input data through the input module; The input data is processed using the AI ​​engine module. Results visualization includes generating a postoperative patient facial visualization model predicted by the AI ​​engine module based on the input data and / or various factors; and displaying the predicted postoperative patient facial visualization model through a visualization module.

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