CN117076958A

CN117076958A - Treatment parameter recommendation system

Info

Publication number: CN117076958A
Application number: CN202311341425.4A
Authority: CN
Inventors: 宋硕; 彭玉家; 雷晓兵; 丁毅; 李亚楠
Original assignee: Hunan Peninsula Medical Technology Co ltd
Current assignee: Hunan Peninsula Medical Technology Co ltd
Priority date: 2023-10-17
Filing date: 2023-10-17
Publication date: 2023-11-17

Abstract

The application discloses a treatment parameter recommendation system, which relates to the technical field of digital medical treatment, and comprises a skin image analysis module, an associated user matching module and a treatment parameter matching module; the skin image analysis module is used for acquiring an initial skin image before treatment of the target user; the associated user matching module is used for determining each associated user corresponding to the target user in a preset treatment database according to the initial skin image, wherein the associated user refers to a user with similarity with the initial skin image in the treatment database being greater than the preset similarity; the treatment parameter matching module is used for selecting and summarizing treatment parameters corresponding to a preset number of associated users according to the skin treatment repair degrees corresponding to the associated users, and generating a treatment parameter recommendation list; and the treatment parameter matching module is also used for sending the treatment parameter recommendation list to the medical equipment for display. The application solves the problem of low determination accuracy of the existing treatment parameter determination mode.

Description

Treatment parameter recommendation system

Technical Field

The application relates to the technical field of digital medical treatment, in particular to a treatment parameter recommendation system.

Background

At present, the determination of the treatment parameters of skin wrinkles is usually performed by medical staff according to knowledge of the medical staff, but the manual determination of the treatment parameters depends on the knowledge reserve of the medical staff for skin wrinkles treatment, and the manual determination of the treatment parameters has certain subjectivity and is easy to cause misjudgment, so the determination accuracy of the conventional treatment parameter determination mode is low.

Disclosure of Invention

The application mainly aims to provide a treatment parameter recommendation system, a method, electronic equipment and a readable storage medium, and aims to solve the technical problem that the determination accuracy of the existing treatment parameter determination mode is low.

In order to achieve the above object, the present application provides a treatment parameter recommendation system, which includes a skin image analysis module, an associated user matching module, and a treatment parameter matching module;

the associated user matching module is respectively connected with the skin image analysis module and the treatment parameter matching module;

the skin image analysis module is used for acquiring an initial skin image of a target user before treatment;

The associated user matching module is used for determining each associated user corresponding to the target user in a preset treatment database according to the initial skin image, wherein the associated user is a user with similarity with the initial skin image being greater than preset similarity in the treatment database;

the treatment parameter matching module is used for selecting and summarizing a preset number of treatment parameters corresponding to the associated users according to the skin treatment repair degrees corresponding to the associated users, and generating a treatment parameter recommendation list;

the treatment parameter matching module is also used for sending the treatment parameter recommendation list to medical equipment for display;

wherein, the skin image analysis module includes wrinkle identification unit and skin treatment restoration degree operation unit:

the wrinkle identification unit is connected with the skin treatment repair degree operation unit;

the wrinkle identification unit is used for acquiring target treatment parameters adopted by the target user and acquiring a target skin image after the target user is treated;

the wrinkle recognition unit is further used for extracting initial skin wrinkle information of the initial skin image and target skin wrinkle information of the target skin image based on a skin wrinkle recognition algorithm;

The skin treatment repair degree operation unit is used for determining the target skin treatment repair degree corresponding to the target user according to the initial skin wrinkle information and the target skin wrinkle information;

the skin treatment repair degree operation unit is further configured to store the target user, the initial skin image, the initial skin wrinkle information, the target skin image, the target skin wrinkle information, the target skin treatment repair degree, and the target treatment parameter in association to the treatment database to update the treatment database.

Optionally, the preset similarity includes a preset image similarity, and the associated user matching module is further configured to:

determining the image similarity between the skin image before treatment of each user in the treatment database and the initial skin image based on an image matching algorithm;

and taking each user with the image similarity larger than the preset image similarity as each associated user corresponding to the target user.

Optionally, the preset similarity includes a preset information similarity, and the associated user matching module is further configured to:

extracting initial skin wrinkle information of the initial skin image based on a skin wrinkle recognition algorithm;

Determining the information similarity between skin wrinkle information before treatment of each user and the initial skin wrinkle information in the treatment database;

and taking each user with the information similarity larger than the preset information similarity as each associated user corresponding to the target user.

Optionally, the preset similarity includes a preset image similarity and a preset information similarity, and the associated user matching module is further configured to:

summarizing all users with the information similarity larger than the preset information similarity to obtain a candidate user set;

determining the image similarity between the skin image before treatment of each candidate user in the candidate user set and the initial skin image based on an image matching algorithm;

and taking each candidate user with the image similarity larger than the preset image similarity as each associated user corresponding to the target user.

Optionally, the skin image analysis module further comprises an image separation unit;

The image separation unit is connected with the associated user matching module;

the image separation unit is used for acquiring a user image of the target user acquired based on the image sensor;

the image separation unit is further configured to perform image separation processing on the user image to obtain a foreground image, and use the foreground image as the initial skin image.

Optionally, the skin wrinkle information includes the number of wrinkles or the depth of wrinkles, and the skin treatment repair degree operation unit is further configured to:

calculating the target skin treatment repair degree corresponding to the target user according to the initial wrinkle number and the target wrinkle number;

or, calculating the target skin treatment repair degree corresponding to the target user according to the initial wrinkle depth and the target wrinkle depth.

Optionally, the skin wrinkle information includes the number of wrinkles and the depth of wrinkles, and the skin treatment repair degree operation unit is further configured to:

determining a difference in the number of wrinkles between the initial number of wrinkles and the target number of wrinkles, and determining a difference in the depth of wrinkles between the initial depth of wrinkles and the target depth of wrinkles;

searching the wrinkle number weight corresponding to the wrinkle number difference and the wrinkle depth weight corresponding to the wrinkle depth difference;

Determining a wrinkle number ratio of the wrinkle number difference to the initial wrinkle number, and determining a wrinkle depth ratio of the wrinkle depth difference to the initial wrinkle depth;

calculating the product of the wrinkle quantity ratio and the wrinkle quantity weight to obtain a first skin treatment repair degree;

calculating the product of the wrinkle depth ratio and the wrinkle depth weight to obtain a second skin treatment repair degree;

and calculating the sum of the first skin treatment restoration degree and the second skin treatment restoration degree to obtain the target skin treatment restoration degree corresponding to the target user.

Optionally, the treatment parameter recommendation system further comprises a data storage module;

the data storage module is respectively connected with the skin image analysis module, the associated user matching module and the treatment parameter matching module;

the data storage module is used for storing the treatment database.

Optionally, the data storage module is further configured to:

and performing data cleaning treatment on the treatment database to eliminate repeated data and abnormal data in the treatment database.

The application also provides a treatment parameter recommending method applied to the treatment parameter recommending system, which comprises the following steps:

Acquiring an initial skin image of a target user before treatment;

determining each associated user corresponding to the target user in a preset treatment database according to the initial skin image, wherein the associated user is a user with similarity greater than preset similarity in the treatment database;

selecting and summarizing a preset number of treatment parameters corresponding to the associated users according to the skin treatment repair degrees corresponding to the associated users, and generating a treatment parameter recommendation list;

the treatment parameter recommendation list is sent to medical equipment for display;

acquiring target treatment parameters adopted by the target user, and acquiring a target skin image after treatment of the target user;

extracting initial skin wrinkle information of the initial skin image and target skin wrinkle information of the target skin image based on a skin wrinkle recognition algorithm;

determining a target skin treatment repair degree corresponding to the target user according to the initial skin wrinkle information and the target skin wrinkle information;

the target user, the initial skin image, the initial skin wrinkle information, the target skin image, the target skin wrinkle information, the target skin treatment repair, and the target treatment parameter are stored in association to the treatment database to update the treatment database.

The application also provides an electronic device, which is entity equipment, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the treatment parameter recommendation method as described above.

The present application also provides a readable storage medium, which is a computer readable storage medium having stored thereon a program for implementing a treatment parameter recommendation method, the program for implementing the treatment parameter recommendation method being executed by a processor to implement the steps of the treatment parameter recommendation method as described above.

The application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of a method for recommending treatment parameters as described above.

The application provides a treatment parameter recommendation system, which comprises a skin image analysis module, an associated user matching module and a treatment parameter matching module, wherein the associated user matching module is respectively connected with the skin image analysis module and the treatment parameter matching module.

According to the application, the treatment database is set to store the treatment information of each user, so that under the condition that the skin image analysis module acquires an initial skin image of a target user before treatment, namely under the condition that the skin image analysis module acquires the initial skin image of the user needing to treat skin wrinkles, an associated user similar to the initial skin image of the target user is determined in the treatment database through the associated user matching module, the treatment parameter recommendation is carried out through the skin treatment repair degree of each associated user, namely the treatment effect of each associated user, the process of carrying out the automatic recommendation of the treatment parameters on the skin wrinkles of the user is realized, and medical staff can determine final treatment parameters according to the recommended treatment parameters.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.

In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.

FIG. 1 is a schematic diagram of a treatment parameter recommendation system according to an embodiment of the present application;

fig. 2 is a schematic structural diagram of a treatment parameter recommendation system according to an embodiment of the present application when a data storage module includes a treatment identification unit, a skin image unit and a treatment parameter unit;

FIG. 3 is a schematic view of a first embodiment of a treatment parameter recommendation system according to the present application;

fig. 4 is a schematic structural diagram of a skin image analysis module in the treatment parameter recommendation system according to the first embodiment of the present application, where the skin image analysis module includes an image separation unit, a wrinkle identification unit, and a skin treatment repair degree calculation unit;

FIG. 5 is a flowchart of a second embodiment of a treatment parameter recommendation method according to the present application;

FIG. 6 is a flowchart of a third embodiment of a treatment parameter recommendation method according to the present application;

FIG. 7 is a schematic flow chart of a third embodiment of a treatment parameter recommendation method according to the present application;

Fig. 8 is a schematic diagram of a device structure of a hardware operating environment related to a treatment parameter recommendation method according to an embodiment of the present application.

The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.

Reference numerals illustrate:

Detailed Description

In order to make the above objects, features and advantages of the present application more comprehensible, the following description of the embodiments accompanied with the accompanying drawings will be given in detail. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

Example 1

Based on this, the present application proposes a treatment parameter recommendation system of a first embodiment, referring to fig. 1, the treatment parameter recommendation system includes a skin image analysis module 100, an associated user matching module 200 and a treatment parameter matching module 300, wherein an output end of the skin image analysis module 100 is connected to an input end of the associated user matching module 200, an output end of the associated user matching module 200 is connected to an input end of the treatment parameter matching module 300, the skin image analysis module 100 is configured to obtain an initial skin image before treatment of a target user, the associated user matching module 200 is configured to determine, according to the initial skin image, each associated user corresponding to the target user in a preset treatment database, where the associated user refers to a user whose similarity with the initial skin image in the treatment database is greater than a preset similarity; the treatment parameter matching module 300 is configured to select and collect a preset number of treatment parameters corresponding to the associated users according to skin treatment repair degrees corresponding to the associated users, and generate a treatment parameter recommendation list; the treatment parameter matching module 300 is further configured to send the treatment parameter recommendation list to the medical device for display.

According to the embodiment of the application, the treatment database is arranged to store the treatment information of each user, so that under the condition that the skin image analysis module acquires the initial skin image of the target user before treatment, namely under the condition that the skin image analysis module acquires the initial skin image of the user needing to treat the skin wrinkles, the associated user matching module determines the associated user similar to the initial skin image of the target user in the treatment database, so that the treatment parameter recommendation is carried out through the skin treatment restoration degree of each associated user, namely the treatment effect of each associated user, the process of carrying out the automatic recommendation of the treatment parameters on the skin wrinkles of the user is realized, and medical staff can carry out the final treatment parameter determination according to the recommended treatment parameters.

In a possible implementation manner, the treatment parameter recommendation system further comprises a data storage module 400, wherein an output end of the data storage module 400 is connected to an input end of the skin image analysis module 100, a first input end of the data storage module 400 is connected to an output end of the skin image analysis module 100, a second input end of the data storage module 400 is connected to an output end of the associated user matching module 200, a third input end of the data storage module 400 is connected to an output end of the treatment parameter matching module 300, and the data storage module 400 is used for storing a treatment database.

Further, referring to fig. 2, the data storage module 400 may include a treatment identification unit 401, a skin image unit 402, and a treatment parameter unit 403, where the output end of the treatment identification unit 401, the output end of the skin image unit 402, and the output end of the treatment parameter unit 403 are connected to the input end of the skin image analysis module 100, the first input end of the treatment identification unit 401, the first input end of the skin image unit 402, and the first input end of the treatment parameter unit 403 are connected to the output end of the skin image analysis module 100, the second input end of the treatment identification unit 401, the second input end of the skin image unit 402, and the second input end of the treatment parameter unit 403 are connected to the output end of the associated user matching module 200, the third input end of the treatment identification unit 401, the third input end of the skin image unit 402, and the third input end of the treatment parameter unit 403 are connected to the output end of the treatment parameter matching module 300, the treatment identification unit 401 is used for storing treatment identifications in a treatment database, such as skin treatment repair degrees, user IDs, and the like, the second input end of the skin image unit 402 is used for storing parameters in the treatment database before treatment in the treatment database.

According to the embodiment, the data storage module for storing the treatment database is arranged in the treatment parameter recommendation system, and different data in the treatment database are stored separately through the treatment identification unit, the skin image unit and the treatment parameter unit in the data storage module, so that the data can be extracted from the corresponding unit corresponding to the type of the data when the data is required to be extracted from the treatment database later. So as to improve the efficiency and accuracy of data extraction.

As an example, referring to fig. 3, fig. 3 provides a schematic view of a scenario applied by a treatment parameter recommendation system, where the application scenario provided in fig. 3 includes a medical device and a treatment parameter recommendation system, data transmission between the medical device and the treatment parameter recommendation system is an encrypted transmission mode, the medical device includes a camera 1000, a control system 2000, a networking module 3000 and a display screen 4000, where the camera 1000 is used for collecting user images before and after treatment, the control system 2000 is used for encrypting the collected user images and sending the encrypted user images to the treatment parameter recommendation system, the networking module 3000 is used for implementing data transmission between the medical device and the treatment parameter recommendation system, and the display screen 4000 is used for displaying recommended treatment parameters. The skin image analysis module 100 in the treatment parameter recommendation system acquires the user image before treatment acquired by the camera 1001 in the medical equipment, the skin image analysis module 100, the associated user matching module 200 and the treatment parameter matching module 300 in the treatment parameter recommendation system process the user image to acquire a treatment parameter recommendation list, the treatment parameter recommendation list is displayed on the display screen 4000 of the medical equipment after the treatment parameter recommendation system sends the treatment parameter recommendation list to the medical equipment, the skin image analysis module 100 in the treatment parameter recommendation system acquires the user image after treatment acquired by the camera 1000 in the medical equipment after treatment is completed, the target treatment parameter used by the user is acquired, and the treatment database stored by the data storage module 400 is updated after the treatment parameter recommendation system processes the user image through the skin image analysis module 100 in the treatment parameter recommendation system.

In one possible implementation manner, referring to fig. 4, the skin image analysis module 100 may include an image separation unit 101, a wrinkle identification unit 102, and a skin treatment repair degree calculation unit 103, where an input end of the image separation unit 101 and an input end of the wrinkle identification unit 102 are connected to an output end of the data storage module 400, an output end of the image separation unit 101 is connected to an input end of the associated user matching module 200, an output end of the wrinkle identification unit 102 is connected to an input end of the skin treatment repair degree calculation unit 103, and an output end of the skin treatment repair degree calculation unit 103 is connected to an input end of the data storage module 400; the image separation unit 101 is configured to acquire a user image of a target user acquired based on an image sensor; the image separation unit 101 is further configured to perform image separation processing on the user image to obtain a foreground image, and use the foreground image as an initial skin image; the wrinkle identification unit 102 is used for acquiring target treatment parameters adopted by a target user and acquiring a target skin image after treatment of the target user; the wrinkle recognition unit 102 is further configured to extract initial skin wrinkle information of an initial skin image and target skin wrinkle information of a target skin image based on a skin wrinkle recognition algorithm; the skin treatment repair degree operation unit 103 is used for determining a target skin treatment repair degree corresponding to a target user according to the initial skin wrinkle information and the target skin wrinkle information; the skin treatment repair degree calculation unit 103 is further configured to store the target user, the initial skin image, the initial skin wrinkle information, the target skin image, the target skin wrinkle information, the target skin treatment repair degree, and the target treatment parameter in association to the treatment database to update the treatment database.

As an example, the image separation unit 101 may be composed of an image division circuit, the wrinkle recognition unit 102 may be composed of an image gradation processing circuit and an image binary processing circuit, and the skin treatment repair degree operation unit 103 may be composed of an addition operation circuit, a subtraction operation circuit, and a division operation circuit.

Example two

The present application also provides a treatment parameter recommendation method, which is applied to the treatment parameter recommendation system described above, please refer to fig. 5, and with reference to fig. 1 to 4, the treatment parameter recommendation method includes:

step S10, acquiring an initial skin image of a target user before treatment;

the target user is a user who needs to perform skin wrinkle treatment, and the number of the target users may be one or more, and the embodiment is not limited thereto. The initial skin image is used for representing the skin condition of the target user before treatment, and the initial skin image can be skin images of different parts of the face, the eyes, the forehead and the like of the user. The initial skin image before the treatment of the target user may be acquired in real time or periodically, which is not limited in this embodiment.

Step S20, determining each associated user corresponding to the target user in a preset treatment database according to the initial skin image, wherein the associated user is a user with similarity with the initial skin image being greater than preset similarity in the treatment database;

the correspondence between different users and treatment information is recorded in the treatment database, and the treatment information may include a skin image before treatment of the user, a skin image after treatment of the user, skin wrinkle information before treatment of the user, skin wrinkle information after treatment of the user, skin treatment repair degree of the user, treatment parameters adopted by the user, and the like.

As an example, the step of determining, according to the initial skin image, each associated user corresponding to the target user in a preset treatment database includes: and according to the initial skin image, the treatment information of all users in the treatment database is scanned completely, and the users with the similarity larger than the preset similarity with the initial skin image are determined and used as the associated users corresponding to the target users.

Step S30, selecting and summarizing a preset number of treatment parameters corresponding to the associated users according to the skin treatment repair degrees corresponding to the associated users, and generating a treatment parameter recommendation list;

It should be noted that the skin treatment repair degree refers to a repair condition of skin wrinkles, that is, a treatment effect of skin wrinkles, and the treatment parameter recommendation list may be used to record treatment parameters corresponding to each selected associated user, or may be used to record treatment parameters corresponding to each selected associated user and skin treatment repair degrees corresponding to the associated user. When summarizing the selected treatment parameters, the selected treatment parameters may be sequentially summarized according to the magnitude order of the skin treatment repair degrees, or may be sequentially summarized, which is not limited in this embodiment.

As an example, the step of selecting and summarizing a preset number of treatment parameters corresponding to the associated users according to the skin treatment repair degrees corresponding to the associated users, and generating a treatment parameter recommendation list includes: and sequencing the treatment parameters corresponding to the associated users according to the skin treatment restoration degree corresponding to the associated users, selecting and summarizing a preset number of treatment parameters corresponding to the associated users according to the sequence from high to low of the sequencing size, and generating the treatment parameter recommendation list.

As another example, to facilitate better determination of treatment parameters by medical staff, a treatment parameter recommendation list including treatment parameters and treatment repair degrees corresponding to the treatment parameters may be generated, so that medical staff may assist in determining treatment parameters according to the treatment repair degrees, where, according to the skin treatment repair degrees corresponding to each associated user, a preset number of treatment parameters corresponding to the associated users are selected and summarized, and the step of generating the treatment parameter recommendation list includes: according to the skin treatment restoration degree corresponding to each associated user, sequencing the treatment parameters corresponding to each associated user, selecting a preset number of treatment parameters corresponding to the associated users according to the sequence from high to low of the sequencing size, correlating the selected treatment parameters corresponding to each associated user with the skin treatment restoration degree corresponding to the associated user, and generating the treatment parameter recommendation list.

And step S40, the treatment parameter recommendation list is sent to medical equipment for display.

Because the treatment parameters recorded in the treatment parameter recommendation list have a treatment parameter (optimal treatment parameter) with the maximum skin treatment restoration degree, namely the treatment parameter with the best treatment effect, in order to facilitate medical staff to better determine the treatment parameter, when the treatment parameter recommendation list is displayed on medical equipment, the display effect of the optimal treatment parameter in the treatment parameter recommendation list can be enhanced, for example, the display font of the optimal treatment parameter is thickened.

The embodiment of the application provides a treatment parameter recommendation method, which comprises the steps of firstly acquiring an initial skin image of a target user before treatment, then determining each associated user corresponding to the target user in a preset treatment database according to the initial skin image, namely determining a user with similarity greater than the preset similarity with the initial skin image in the treatment database as the associated user of the target user, then selecting and summarizing treatment parameters corresponding to the associated users with the preset number of skin treatment restoration degrees in front according to the skin treatment restoration degrees corresponding to each associated user, generating a treatment parameter recommendation list, and finally transmitting the treatment parameter recommendation list to medical equipment for display. According to the embodiment of the application, the treatment database is set to store the treatment information of each user, so that under the condition that the initial skin image of the target user before treatment is acquired, namely, under the condition that the initial skin image of the user needing to treat the skin wrinkles is acquired, the associated user similar to the initial skin image of the target user is determined in the treatment database, so that the treatment parameter recommendation is carried out according to the skin treatment repair degree of each associated user, namely, the treatment effect of each associated user, the process of carrying out automatic treatment parameter recommendation on the skin wrinkles of the user is realized, and medical staff can determine the final treatment parameters according to the recommended treatment parameters.

In one possible implementation manner, the preset similarity includes a preset image similarity, and the step of determining, according to the initial skin image, each associated user corresponding to the target user in a preset treatment database includes:

step S21, determining the image similarity between the skin image before treatment of each user in the treatment database and the initial skin image based on an image matching algorithm;

it should be noted that the image matching algorithm may be a K-means clustering algorithm, which is also referred to as a K-means algorithm, and the algorithm idea is to randomly select K samples from a sample set as cluster centers, calculate distances between all samples and the K cluster centers, divide each sample into clusters where the cluster center closest to the sample is located, and then calculate cluster centers of each new cluster until the obtained cluster center changes tend to be stable, so as to obtain K clusters.

And S22, taking each user with the image similarity larger than the preset image similarity as each associated user corresponding to the target user.

In this embodiment, the image similarity between the skin image before treatment and the initial skin image of each user in the treatment database is determined by an image matching algorithm, and then each user with the image similarity greater than the preset image similarity is used as each associated user corresponding to the target user, so as to screen out the user similar to the skin condition of the target user before treatment in the treatment database. According to the method and the device for determining the skin condition of the target user before treatment, the initial skin image is matched with the skin image of each user before treatment in the treatment database, so that the user similar to the skin condition of the target user before treatment can be accurately determined through the similarity of the images, and the accuracy of the determination of the associated user is ensured.

In one possible implementation manner, the preset similarity includes a preset information similarity, and the step of determining, according to the initial skin image, each associated user corresponding to the target user in a preset treatment database includes:

step E21, extracting initial skin wrinkle information of the initial skin image based on a skin wrinkle recognition algorithm;

it should be noted that the initial skin wrinkle information is used to characterize the skin wrinkle information of the target user before treatment, and the skin wrinkle information may include the number of wrinkles, the depth of wrinkles, the area of wrinkles, the shape of wrinkles, and the like.

As an example, the step of extracting initial skin wrinkle information of the initial skin image based on a skin wrinkle recognition algorithm includes: and performing image gray processing on the initial skin image to obtain a gray skin image, and performing binarization calculation on the gray skin image to extract and obtain the initial skin wrinkle information.

Step E22, determining the information similarity between the skin wrinkle information before treatment of each user and the initial skin wrinkle information in the treatment database;

as an example, the step of determining the information similarity of skin wrinkle information before treatment with the initial skin wrinkle information for each user in the treatment database includes: for any user in the treatment database, taking various types of information in skin wrinkle information before treatment of the user as matrix row elements, and taking various types of information in the initial skin wrinkle information as matrix column elements, so as to generate an information comparison matrix, wherein the information comparison matrix comprises a plurality of groups of diagonal units; and calculating the information editing probability of each group of diagonal units in the information comparison matrix to determine the total editing probability of the information comparison matrix, wherein the total editing probability is used as the information similarity of the skin wrinkle information before the treatment of the user and the initial skin wrinkle information, and the information editing probability refers to the operation times required for editing two types of information into information with the same content.

For example, assuming that skin wrinkle information includes the number of wrinkles, the depth of wrinkles, and the area of wrinkles, the number of wrinkles, the depth of wrinkles, and the area of wrinkles before treatment by the user in the treatment database may be respectively taken as a matrix row element, and the initial number of wrinkles, the initial depth of wrinkles, and the area of wrinkles of the target user may be respectively taken as a matrix column element to generate the information comparison matrix, and when the information comparison matrix is edited, assuming that the number of wrinkles before treatment by the user a in the treatment database is 5, the initial number of wrinkles by the target user is 10, and when the number of wrinkles before treatment by the user a is added to 1 in the information comparison matrix once, a total of editing operations may be required to be performed 5 times, so that the number of wrinkles before treatment by the user a coincides with the initial number of wrinkles by the target user.

And E23, taking each user with the information similarity larger than the preset information similarity as each associated user corresponding to the target user.

In this embodiment, initial skin wrinkle information of an initial skin image is extracted through a skin wrinkle recognition algorithm, then information similarity between skin wrinkle information before treatment of each user in a treatment database and the initial skin wrinkle information is determined, and then each user with the information similarity greater than the preset information similarity is used as each associated user corresponding to a target user, so as to screen out a user similar to the skin condition of the target user before treatment in the treatment database. In the embodiment, the initial skin wrinkle information of the initial skin image is extracted and compared with the skin wrinkle information before treatment of each user in the treatment database, so that the user similar to the skin condition of the target user before treatment is accurately determined through the similarity of the wrinkle information, the accuracy of determining the associated user is ensured, and the accuracy of determining the similar user through the wrinkle information is higher compared with the accuracy of determining the similar user through the matching image.

In one possible implementation manner, the preset similarity includes a preset image similarity and a preset information similarity, and the step of determining, according to the initial skin image, each associated user corresponding to the target user in a preset treatment database includes:

step F21, extracting initial skin wrinkle information of the initial skin image based on a skin wrinkle recognition algorithm;

step F22, determining the information similarity between the skin wrinkle information before treatment of each user and the initial skin wrinkle information in the treatment database;

step F23, summarizing all users with the information similarity larger than the preset information similarity to obtain a candidate user set;

it should be noted that, the candidate user set includes a plurality of candidate users, and the information similarity between the skin wrinkle information before treatment of each candidate user and the initial skin wrinkle information is greater than the preset information similarity.

Step F24, determining the image similarity between the skin image before treatment of each candidate user in the candidate user set and the initial skin image based on an image matching algorithm;

and F25, taking each candidate user with the image similarity larger than the preset image similarity as each associated user corresponding to the target user.

In this embodiment, initial skin wrinkle information of an initial skin image is extracted through a skin wrinkle recognition algorithm, then information similarity between skin wrinkle information before treatment of each user in a treatment database and the initial skin wrinkle information is determined, then each user with information similarity greater than preset information similarity is summarized to obtain a candidate user set so as to achieve primary screening of similar users, then image similarity between the skin image before treatment of each candidate user in the candidate user set and the initial skin image is determined through an image matching algorithm, and then each user with image similarity greater than the preset image similarity is used as each associated user corresponding to a target user so as to achieve secondary screening of the similar users. Therefore, the embodiment determines each associated user corresponding to the target user by combining the skin wrinkle recognition algorithm and the image matching algorithm, so that the determined each associated user meets the condition that the information similarity is greater than the preset information similarity and meets the condition that the image similarity is greater than the preset image similarity, and compared with the condition that the similar user is determined by matching the images or the accuracy of determining the similar user by the wrinkle information is higher.

In one possible implementation, the step of acquiring an initial skin image of the target user before treatment includes:

step S11, acquiring a user image of the target user acquired based on an image sensor;

the image sensor may include a camera, a device having a photographing function, and the like.

And step S12, performing image separation processing on the user image to obtain a foreground image, and taking the foreground image as the initial skin image.

It should be noted that, the image separation processing may be data processing such as optical flow algorithm, low rank decomposition and mixed gaussian modeling, where the purpose of the image separation processing is to separate the foreground and the background of the user image, where the foreground image only includes the skin wrinkle image of the target user, and it is understood that, in general, the user image collected by the image sensor includes the foreground image and the background image, in order to improve the determination efficiency and the determination accuracy of each associated user corresponding to the target user in the subsequent determination, the user image collected by the image sensor may be separated from the foreground and the background to obtain the foreground image only including the skin wrinkle image of the target user, and since the foreground image includes less image information relative to the image information included in the user image, the processing time of the foreground image may be shorter than the processing time of the user image, thereby improving the determination efficiency of each associated user corresponding to the target user.

Example III

In another embodiment of the present application, the same or similar contents as those of the above embodiment can be referred to the above description, and the description thereof will be omitted. On this basis, referring to fig. 6, after the step of sending the recommended list of treatment parameters to the medical device for display, the method for recommending treatment parameters further includes:

step S50, acquiring target treatment parameters adopted by the target user, and acquiring a target skin image after treatment of the target user;

it should be noted that the target skin image is used to represent the skin condition of the target user after treatment, and the target skin image may be skin images of different parts such as the face, the eyes, the forehead, etc. The target skin image after the treatment of the target user may be acquired in real time or periodically, which is not limited in this embodiment.

Step S60, extracting initial skin wrinkle information of the initial skin image and target skin wrinkle information of the target skin image based on a skin wrinkle recognition algorithm;

it should be noted that the target skin wrinkle information is used to characterize the skin wrinkle information of the target user after treatment.

Step S70, determining a target skin treatment repair degree corresponding to the target user according to the initial skin wrinkle information and the target skin wrinkle information;

as an example, the skin wrinkle information includes a wrinkle area, and the step of determining the target skin treatment repair degree corresponding to the target user according to the initial skin wrinkle information and the target skin wrinkle information includes: and calculating the difference between the initial wrinkle area and the target wrinkle area to obtain a wrinkle area difference, and calculating the ratio of the wrinkle area difference to the initial wrinkle area to obtain the target skin treatment repair degree corresponding to the target user.

Step S80, storing the target user, the initial skin image, the initial skin wrinkle information, the target skin image, the target skin wrinkle information, the target skin treatment repair degree, and the target treatment parameter in association with the treatment database to update the treatment database.

In order to avoid repeated data or abnormal data in the treatment database, after the treatment database is updated, the treatment database can be subjected to data cleaning treatment so as to eliminate the repeated data or abnormal data in the treatment database and reduce the occupation of useless data on the storage space of the treatment database.

In this embodiment, first, the target treatment parameters adopted by the target user are acquired, the target skin image after the target user is treated is acquired, then the initial skin wrinkle information of the initial skin image and the target skin wrinkle information of the target skin image are extracted through the skin wrinkle recognition algorithm, then the treatment effect of the target user adopting the target treatment parameters, namely, the target skin treatment repair degree, is determined according to the initial skin wrinkle information and the target skin wrinkle information, and finally the target user, the initial skin image, the initial skin wrinkle information, the target skin image, the target skin wrinkle information, the target skin treatment repair degree and the target treatment parameters are stored in a treatment database in an associated manner so as to update the treatment database, so that the treatment database is updated once after each time of skin wrinkle treatment of the user is performed, the data amount recorded in the treatment database can be increased continuously, and richer treatment data can be provided for the subsequent skin wrinkle treatment, and more accurate treatment parameters are recommended to medical staff.

In one possible implementation, the skin wrinkle information includes a wrinkle number or a wrinkle depth, and the step of determining a target skin treatment repair corresponding to the target user according to the initial skin wrinkle information and the target skin wrinkle information includes:

Step S71, calculating the target skin treatment repair degree corresponding to the target user according to the initial wrinkle number and the target wrinkle number;

as an example, the step of calculating the target skin treatment repair degree corresponding to the target user according to the initial number of wrinkles and the target number of wrinkles includes: and calculating the difference between the initial number of wrinkles and the target number of wrinkles to obtain a difference between the number of wrinkles, and calculating the ratio of the difference between the number of wrinkles and the initial number of wrinkles to obtain the target skin treatment repair degree corresponding to the target user.

Step S72, or, calculating the target skin treatment repair degree corresponding to the target user according to the initial wrinkle depth and the target wrinkle depth.

As an example, the step of calculating the target skin treatment repair degree corresponding to the target user according to the initial wrinkle depth and the target wrinkle depth includes: and calculating the difference between the initial wrinkle depth and the target wrinkle depth to obtain a wrinkle depth difference, and calculating the ratio of the wrinkle depth difference to the initial wrinkle depth to obtain the target skin treatment repair degree corresponding to the target user.

In one possible implementation, the skin wrinkle information includes a wrinkle number and a wrinkle depth, and the step of determining a target skin treatment repair corresponding to the target user according to the initial skin wrinkle information and the target skin wrinkle information includes:

step E71, determining a difference between the number of wrinkles of the initial number of wrinkles and the number of wrinkles of the target number of wrinkles, and determining a difference between the depth of wrinkles of the initial number of wrinkles and the depth of wrinkles of the target number of wrinkles;

step E72, searching the wrinkle number weight corresponding to the wrinkle number difference value and the wrinkle depth weight corresponding to the wrinkle depth difference value;

the number of wrinkles is the degree of influence of the number of wrinkles on the skin treatment repair, the depth of wrinkles is the degree of influence of the depth of wrinkles on the skin treatment repair, and the degree of influence of the depth of wrinkles and the number of wrinkles on the skin treatment repair are in positive correlation with the respective change values (namely, the difference between the number of wrinkles and the difference between the depth of wrinkles).

As an example, a table may be constructed to record the correspondence between the number of wrinkles and the correspondence between the depth of wrinkles and the depth of wrinkles, and the step of searching for the number of wrinkles and the depth of wrinkles corresponding to the number of wrinkles includes: and searching the wrinkle number weight corresponding to the wrinkle number difference and the wrinkle depth weight corresponding to the wrinkle depth difference in a preset configuration table.

Step E73, determining a wrinkle number ratio of the wrinkle number difference value and the initial wrinkle number, and determining a wrinkle depth ratio of the wrinkle depth difference value and the initial wrinkle depth;

step E74, calculating the product of the wrinkle quantity ratio and the wrinkle quantity weight to obtain a first skin treatment repair degree;

step E75, calculating the product of the wrinkle depth ratio and the wrinkle depth weight to obtain a second skin treatment repair degree;

and E76, calculating the sum of the first skin treatment restoration degree and the second skin treatment restoration degree to obtain the target skin treatment restoration degree corresponding to the target user.

In this embodiment, when determining the target skin treatment repair degree corresponding to the target user, the influence of the wrinkle depth and the number of wrinkles on the finally determined target skin treatment repair degree is considered, firstly, determining the difference between the initial number of wrinkles and the number of wrinkles, and the difference between the initial number of wrinkles and the depth of wrinkles, then searching the weight of the number of wrinkles corresponding to the difference between the initial number of wrinkles, and the weight of the depth of wrinkles corresponding to the difference between the depth of wrinkles, then determining the ratio between the number of wrinkles and the number of wrinkles, and the ratio between the depth of wrinkles and the depth of wrinkles, then calculating the product of the ratio between the number of wrinkles and the weight of the number of wrinkles, obtaining the first skin treatment repair degree, and calculating the product of the ratio between the depth of wrinkles and the weight of the depth of wrinkles, obtaining the second skin treatment repair degree, and taking the sum of the first skin treatment repair degree and the second skin treatment repair degree as the target skin treatment repair degree corresponding to the target user. According to the embodiment, the influence degree of the number of the wrinkles on the skin treatment restoration degree and the influence degree of the depth of the wrinkles on the skin treatment restoration degree are respectively determined through the difference value of the number of the wrinkles and the difference value of the depth of the wrinkles, so that the number of the wrinkles and the ratio of the depth of the wrinkles are weighted through the weight of the number of the wrinkles and the weight of the depth of the wrinkles respectively, and the final target skin treatment restoration degree is determined, and therefore accurate determination of treatment parameters is achieved. The present embodiment has higher accuracy in determining the target skin treatment repair degree corresponding to the target user by the number of wrinkles or the depth of wrinkles than the aforementioned one.

In order to facilitate understanding of the technical concept or the technical principle of the present application, please refer to fig. 7, fig. 7 provides a schematic implementation flow diagram of a medical device (device side in the figure) and a treatment parameter recommendation system (cloud side in the figure), the device side collects user images of a target user before treatment, then sends the user images before treatment to the cloud side for processing, after receiving the user images before treatment, the cloud side performs image separation processing on the user images before treatment to obtain an initial skin image, then analyzes skin conditions of the initial skin image through a skin wrinkle recognition algorithm, matches similar users (associated users) corresponding to the target user through an image matching algorithm, sorts each similar user according to the height of treatment effects, selects a certain number of treatment parameters corresponding to the similar users after sorting to generate a treatment parameter recommendation list, then sends the treatment parameter recommendation list to the device side for displaying, records target treatment parameters adopted by the target user, and sends the user images of the target user after treatment together with the user images of the target user collected by the device side for processing, after receiving the user images after treatment, analyzes skin conditions of the initial skin image after the user images after treatment, and finally analyzes skin images after separation of the target images according to the skin images after the initial skin images.

It should be noted that the above specific embodiments are only for understanding the present application, and do not limit the method of recommending the therapeutic parameters of the present application, and many simple changes based on this technical concept are all within the scope of the present application.

Example IV

The embodiment of the application provides electronic equipment, which comprises: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the treatment parameter recommendation method of the first embodiment.

Referring now to fig. 8, a schematic diagram of an electronic device suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistant: personal digital assistants), PADs (Portable Application Description: tablet computers), PMPs (Portable Media Player: portable multimedia players), vehicle terminals (e.g., car navigation terminals), and the like, as well as stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 8 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.

As shown in fig. 8, the electronic apparatus may include a processing device 1001 (e.g., a central processing unit, a graphics processor, or the like) that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access Memory (RAM: random Access Memory) 1004. In the RAM1004, various programs and data required for the operation of the electronic device are also stored. The processing device 1001, the ROM1002, and the RAM1004 are connected to each other by a bus 1005. An input/output (I/O) interface 1006 is also connected to the bus. In general, the following systems may be connected to the I/O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, and the like; an output device 1008 including, for example, a liquid crystal display (LCD: liquid Crystal Display), a speaker, a vibrator, and the like; storage device 1003 including, for example, a magnetic tape, a hard disk, and the like; and communication means 1009. The communication means 1009 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. While electronic devices having various systems are shown in the figures, it should be understood that not all of the illustrated systems are required to be implemented or provided. More or fewer systems may alternatively be implemented or provided.

In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. The above-described functions defined in the method of the embodiment of the present disclosure are performed when the computer program is executed by the processing device 1001.

The electronic equipment provided by the invention can solve the technical problem of low determination accuracy of the existing treatment parameter determination mode by adopting the treatment parameter recommendation method in the embodiment. Compared with the prior art, the beneficial effects of the electronic device provided by the embodiment of the invention are the same as those of the treatment parameter recommending method provided by the embodiment, and other technical features of the electronic device are the same as those disclosed by the method of the previous embodiment, and are not repeated here.

It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the description of the above embodiments, particular features, structures, materials, or characteristics may be combined in any suitable manner in any one or more embodiments or examples.

The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Example five

An embodiment of the present invention provides a computer readable storage medium having computer readable program instructions stored thereon for executing the treatment parameter recommendation method in the second embodiment.

The computer readable storage medium according to the embodiments of the present invention may be, for example, a usb disk, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access Memory (RAM: random Access Memory), a Read-Only Memory (ROM: read Only Memory), an erasable programmable Read-Only Memory (EPROM: erasable Programmable Read Only Memory or flash Memory), an optical fiber, a portable compact disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this embodiment, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, or device. Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: wire, fiber optic cable, RF (Radio Frequency), and the like, or any suitable combination of the foregoing.

The above-described computer-readable storage medium may be contained in an electronic device; or may exist alone without being assembled into an electronic device.

The computer-readable storage medium carries one or more programs that, when executed by an electronic device, cause the electronic device to: acquiring an initial skin image of a target user before treatment; determining each associated user corresponding to the target user in a preset treatment database according to the initial skin image, wherein the associated user is a user with similarity greater than preset similarity in the treatment database; selecting and summarizing a preset number of treatment parameters corresponding to the associated users according to the skin treatment repair degrees corresponding to the associated users, and generating a treatment parameter recommendation list; the treatment parameter recommendation list is sent to medical equipment for display; acquiring target treatment parameters adopted by the target user, and acquiring a target skin image after treatment of the target user; extracting initial skin wrinkle information of the initial skin image and target skin wrinkle information of the target skin image based on a skin wrinkle recognition algorithm; determining a target skin treatment repair degree corresponding to the target user according to the initial skin wrinkle information and the target skin wrinkle information; the target user, the initial skin image, the initial skin wrinkle information, the target skin image, the target skin wrinkle information, the target skin treatment repair, and the target treatment parameter are stored in association to the treatment database to update the treatment database.

Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN: local Area Network) or a wide area network (WAN: wide Area Network), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The modules described in the embodiments of the present disclosure may be implemented in software or hardware. Wherein the name of the module does not constitute a limitation of the unit itself in some cases.

The readable storage medium provided by the application is a computer readable storage medium, and the computer readable storage medium stores computer readable program instructions for executing the treatment parameter recommendation method, so that the technical problem of low determination accuracy of the existing treatment parameter determination mode can be solved. Compared with the prior art, the beneficial effects of the computer readable storage medium provided by the embodiment of the present application are the same as those of the treatment parameter recommendation method provided by the first embodiment, and are not described herein.

Example six

The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program realizes the steps of the treatment parameter recommending method when being executed by a processor.

The computer program product provided by the application can solve the technical problem that the determination accuracy of the existing treatment parameter determination mode is low. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as those of the treatment parameter recommendation method provided by the above embodiment, and are not described herein.

The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the application, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein, or any application, directly or indirectly, within the scope of the application.

Claims

1. The treatment parameter recommending system is characterized by comprising a skin image analyzing module, an associated user matching module and a treatment parameter matching module;

2. The treatment parameter recommendation system of claim 1, wherein the preset similarity comprises a preset image similarity, the associated user matching module further configured to:

3. The treatment parameter recommendation system of claim 1, wherein the preset similarity comprises a preset information similarity, the associated user matching module further configured to:

4. The treatment parameter recommendation system of claim 1, wherein the preset similarity comprises a preset image similarity and a preset information similarity, the associated user matching module further configured to:

5. The treatment parameter recommendation system of claim 1, wherein said skin image analysis module further comprises an image separation unit;

6. The treatment parameter recommendation system of claim 1, wherein the skin wrinkle information includes a number of wrinkles or a depth of wrinkles, and the skin treatment repair degree calculation unit is further configured to:

7. The treatment parameter recommendation system of claim 1, wherein skin wrinkle information includes a number of wrinkles and a depth of wrinkles, the skin treatment repair degree calculation unit further configured to:

8. The therapy parameter recommendation system of any one of claims 1 to 7, further comprising a data storage module;

the data storage module is used for storing the treatment database.

9. The therapy parameter recommendation system of claim 8, wherein said data storage module is further configured to: