CN-121987338-A - Laser therapeutic apparatus, laser therapeutic apparatus operation control device and storage medium

CN121987338ACN 121987338 ACN121987338 ACN 121987338ACN-121987338-A

Abstract

The application relates to a laser therapeutic apparatus, a laser therapeutic apparatus operation control device and a storage medium. The laser therapeutic instrument comprises a processor and a memory, wherein the memory is used for storing a computer program, the processor is used for acquiring static characteristics and dynamic characteristics of a target object when running the computer program, acquiring a change trend prediction result of the target object based on the static characteristics and the dynamic characteristics and combining a tissue characteristic map and a prediction model, the tissue characteristic map comprises static characteristic reference values of different tissue types/skin types and a historical change rule curve of the dynamic characteristics along with time, the prediction model is obtained based on constitutive equation training of the target object, working parameters when the regions of the target object are operated are determined based on the change trend prediction result and combining an energy gradient distribution algorithm, and real-time parameters of corresponding components in the laser therapeutic instrument are adjusted based on the working parameters to finish the treatment of the target object. Thus, the treatment accuracy and stability are improved.

Inventors

ZHANG HONGBO
ZHANG KAI
BAI SONGHUA

Assignees

北京萨诺光电科技发展有限公司

Dates

Publication Date: 20260508
Application Date: 20260409

Claims (10)

1. The laser therapeutic apparatus is characterized by comprising a processor and a memory, wherein the memory is used for storing a computer program, and the processor executes the following steps when running the computer program: Acquiring static characteristics and dynamic characteristics of a target object, wherein the static characteristics represent optical characteristic parameters of the target object, and the dynamic characteristics represent dynamic variation of the target object in the treatment process; Based on the static characteristics and the dynamic characteristics, combining a tissue characteristic map and a prediction model to obtain a change trend prediction result of the target object, wherein the tissue characteristic map comprises static characteristic reference values of different tissue types/skin types and a historical change rule curve of the dynamic characteristics along with time; Based on the change trend prediction result, working parameters when each region of the target object is operated are determined by combining an energy gradient distribution algorithm; Based on the working parameters, real-time parameters of corresponding components in the laser therapeutic instrument are adjusted, and the treatment of the target object is completed.
2. The laser therapeutic apparatus according to claim 1, wherein the obtaining the change trend prediction result of the target object based on the static feature and the dynamic feature in combination with a tissue characteristic map and a prediction model includes: matching the static features with the tissue characteristic map to obtain a target tissue type and a corresponding dynamic change reference trend; Inputting the static features and the dynamic features into the prediction model to obtain a candidate change trend prediction result; and obtaining the change trend prediction result based on the candidate change trend prediction result and the dynamic change reference trend.
3. The laser therapeutic apparatus of claim 1, wherein said matching the static feature with the tissue characteristic map to obtain a target tissue class and a corresponding dynamic change baseline trend comprises: Screening out matching key indexes and non-core indexes from the static characteristics, and calculating the similarity between the matching key indexes and static characteristic reference values in the tissue characteristic map; screening candidate units from the tissue characteristic map according to the similarity; comparing the fit degree of the non-core index when the candidate units are a plurality of; And screening the target tissue class from the candidate units based on the fit degree, and determining the corresponding dynamic change reference trend.
4. The laser therapeutic apparatus according to claim 1, wherein the prediction model is a physical information neural network, and the training method of the prediction model comprises: Acquiring sample data and extracting sample characteristics, wherein the sample characteristics comprise static sample characteristics and dynamic sample characteristics; Constructing the constitutive equation of the target object based on deformation and strain, mechanical properties and stress relaxation of the tissue under the action of laser; training an initial network based on the sample characteristics, embedding the constitutive equation as a constraint condition into a network loss function, and iterating the initial network until loss values are converged to obtain the prediction model.
5. The laser therapeutic apparatus according to claim 1, wherein the determining of the operation parameters when operating the regions of the target object based on the change trend prediction result in combination with an energy gradient distribution algorithm includes: Dividing a laser spot into a plurality of independent micro areas through a spot dividing algorithm; Determining static feature weights and dynamic trend weights based on the tissue absorption coefficient predicted values in the change trend predicted results; Determining a safety correction coefficient based on a temperature predicted value in the change trend predicted result; Determining a target power density in the operating parameter based on the base power density of each individual micro-zone, the static feature weight, the dynamic trend weight, and the safety correction coefficient; And determining the target laser wavelength in the working parameters based on the predicted value of the tissue absorption coefficient in the predicted result of the variation trend.
6. The laser therapeutic apparatus of claim 4, wherein the determining the target laser wavelength in the operating parameter based on the predicted value of the tissue absorption coefficient in the predicted trend result of the change comprises: determining a penetration depth prediction result based on the tissue absorption coefficient prediction value, the current static absorption coefficient and the micro-region static thickness; Substituting the tissue characteristic spectrum to be matched based on the penetration depth prediction result to obtain the target laser wavelength.
7. The laser therapeutic apparatus of claim 4, wherein said adjusting real-time parameters of corresponding components in the laser therapeutic apparatus based on the operating parameters comprises: mapping the target power density into a power control signal through a linear mapping formula; And mapping the penetration depth prediction result into a focusing mirror control signal through a mapping formula of the penetration depth and the focusing mirror, wherein the focusing mirror control signal comprises a position control signal and/or an angle control signal.
8. The laser therapeutic apparatus of claim 4, wherein the expression of the network loss function is as follows: ; ; ; Wherein, the Indicating a data loss; Indicating physical loss, determining based on the constitutive equation; n indicates the number of training samples; indicating the measured tissue characteristic value; indicating a predicted tissue characteristic value; m indicates the number of physical constraint sampling points; Indicating mechanical stress of the tissue; Indicating a relaxation time; Indicating a dynamic elastic modulus; indicating tissue strain.
9. A laser therapeutic apparatus operation control device, characterized by being applied to a laser therapeutic apparatus, comprising: The system comprises an acquisition module, a treatment module and a treatment module, wherein the acquisition module is used for acquiring static characteristics and dynamic characteristics of a target object, wherein the static characteristics represent optical characteristic parameters of the target object; The prediction module is used for obtaining a change trend prediction result of the target object based on the static characteristics and the dynamic characteristics and combining a tissue characteristic map and a prediction model, wherein the tissue characteristic map comprises static characteristic reference values of different tissue types/skin types and a historical change rule curve of the dynamic characteristics along with time; the analysis module is used for determining working parameters when each region of the target object is operated based on the change trend prediction result and in combination with an energy gradient distribution algorithm; And the adjusting module is used for adjusting the real-time parameters of the corresponding components in the laser therapeutic instrument based on the working parameters to finish the treatment of the target object.
10. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor performs the steps performed by the laser therapy apparatus of any of claims 1 to 8.

Description

Laser therapeutic apparatus, laser therapeutic apparatus operation control device and storage medium Technical Field The application relates to the technical field of data processing, in particular to a laser therapeutic apparatus, a laser therapeutic apparatus operation control device and a storage medium. Background The carbon dioxide laser therapeutic apparatus realizes the burning, cutting, carbonization and physiotherapy of the tissues by virtue of the wavelength and the strong absorption characteristic of the moisture in the biological tissues through the photo-thermal effect, and is widely applied to the clinical fields of dermatology, plastic surgery, ophthalmology and the like, and becomes core equipment for the treatment of removing spots, scars, tissue repair and the like. However, the existing carbon dioxide laser therapeutic apparatus still has a plurality of technical defects in clinical application, which restricts the further improvement of the treatment precision, safety and curative effect stability, for example, the precision control difficulty of the treatment process is large, the time, position, angle and other key operation factors of laser irradiation can directly influence the precision and curative effect of energy action, while the existing equipment lacks dynamic adaptation capability to these factors, and the problems of insufficient treatment or excessive damage and the like are caused by the deviation of laser energy from a target area due to artificial operation errors or equipment positioning deviation in clinical operation. Disclosure of Invention In view of the above, it is desirable to provide a laser therapeutic apparatus, a laser therapeutic apparatus operation control device, and a storage medium. In a first aspect, the application provides a laser therapeutic apparatus, comprising a processor and a memory, wherein the memory is used for storing a computer program, and the processor executes the following steps when running the computer program: Acquiring static characteristics and dynamic characteristics of a target object, wherein the static characteristics represent optical characteristic parameters of the target object, and the dynamic characteristics represent dynamic variation of the target object in the treatment process; Based on the static characteristics and the dynamic characteristics, combining a tissue characteristic map and a prediction model to obtain a change trend prediction result of the target object, wherein the tissue characteristic map comprises static characteristic reference values of different tissue types/skin types and a historical change rule curve of the dynamic characteristics along with time; Based on the change trend prediction result, working parameters when each region of the target object is operated are determined by combining an energy gradient distribution algorithm; Based on the working parameters, real-time parameters of corresponding components in the laser therapeutic instrument are adjusted, and the treatment of the target object is completed. In one embodiment, the obtaining the change trend prediction result of the target object based on the static feature and the dynamic feature and by combining a tissue characteristic map and a prediction model includes: matching the static features with the tissue characteristic map to obtain a target tissue type and a corresponding dynamic change reference trend; Inputting the static features and the dynamic features into the prediction model to obtain a candidate change trend prediction result; and obtaining the change trend prediction result based on the candidate change trend prediction result and the dynamic change reference trend. In one embodiment, the matching the static feature with the tissue characteristic map to obtain a target tissue class and a corresponding dynamic change reference trend includes: Screening out matching key indexes and non-core indexes from the static characteristics, and calculating the similarity between the matching key indexes and static characteristic reference values in the tissue characteristic map; screening candidate units from the tissue characteristic map according to the similarity; comparing the fit degree of the non-core index when the candidate units are a plurality of; And screening the target tissue class from the candidate units based on the fit degree, and determining the corresponding dynamic change reference trend. In one embodiment, the prediction model is a physical information neural network, and the training mode of the prediction model comprises the following steps: Acquiring sample data and extracting sample characteristics, wherein the sample characteristics comprise static sample characteristics and dynamic sample characteristics; Constructing the constitutive equation of the target object based on deformation and strain, mechanical properties and stress relaxation of the tissue under the action of laser; training an initial net