CN112221021B - Intelligent laser speckle removing control system for dermatology department - Google Patents

Intelligent laser speckle removing control system for dermatology department Download PDF

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CN112221021B
CN112221021B CN202011205861.5A CN202011205861A CN112221021B CN 112221021 B CN112221021 B CN 112221021B CN 202011205861 A CN202011205861 A CN 202011205861A CN 112221021 B CN112221021 B CN 112221021B
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module
image
spot
color spot
color
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CN112221021A (en
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王丹
李曦哲
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Third Xiangya Hospital of Central South University
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Third Xiangya Hospital of Central South University
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/06—Radiation therapy using light
    • A61N5/0613—Apparatus adapted for a specific treatment
    • A61N5/0616—Skin treatment other than tanning
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/44—Detecting, measuring or recording for evaluating the integumentary system, e.g. skin, hair or nails
    • A61B5/441—Skin evaluation, e.g. for skin disorder diagnosis
    • A61B5/444—Evaluating skin marks, e.g. mole, nevi, tumour, scar
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
    • A61F7/00—Heating or cooling appliances for medical or therapeutic treatment of the human body
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/06—Radiation therapy using light
    • A61N5/067—Radiation therapy using light using laser light
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/06—Radiation therapy using light
    • A61N2005/0626—Monitoring, verifying, controlling systems and methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30088—Skin; Dermal
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30196—Human being; Person
    • G06T2207/30201—Face

Abstract

The invention belongs to the technical field of laser spot removal, and discloses a dermatologic intelligent laser spot removal control system and a control method. The invention realizes the determination of the color spot position by collecting the face image, and the accuracy of removing the color spot is better; the method has the advantages that the diameter and depth information of the color spots are acquired, so that the information of the color spots can be mastered, the spot removal is more targeted, and the normal skin is not damaged; the reduction of the patient's pain of dispelling the freckles is realized through the detection to the narcotic drug is absorbed, carries out the cold compress after dispelling the freckles, realizes removing the calm of freckle wound, improves and removes the freckle comfort level, and the patient resumes better.

Description

Intelligent laser speckle removing control system for dermatology department
Technical Field
The invention belongs to the technical field of laser spot removal, and particularly relates to an intelligent laser spot removal control system and method for dermatology.
Background
At present: the spots refer to spots with different colors from the surrounding, belong to pigmentation disorders, are skin diseases which are usually brown on the face or have pigmentation and damage on the face due to the increase of skin melanin, are frequently generated on the cheek and forehead, comprise freckles, coffee spots, sunburn, senile plaques, nevi of Taitian, and nevi of Ipomoea, are commonly seen in women, are related to heredity, solarization and skin aging, and are aggravated by the spots after solarization. The occurrence rate of color spots is high, and ideal treatment is lacked, which is always a great problem of skin cosmetology, and laser treatment provides an ideal treatment method for the color spots. The laser spot removal method is different from the traditional chemical or physical stripping method, can accurately position spot positions, and has obvious effect on spot removal in a targeted manner; the laser spot removing is safe, and no scar is formed on the skin after the spot removing; the laser spot removal does not need hospitalization, the operation time is short, and the wound is light; the laser spot removing method can lighten skin spots in a short time, and the effect is quicker than other spot removing methods.
However, the determination of the laser speckle removing intensity of different color spots at present depends on more experience, the intensity selection is not accurate enough, the problems of skin burn or incomplete speckle removal are easily caused, and the speckle removing effect is poor. Moreover, the state of the color spot cannot be automatically detected after laser treatment, and the deviation is easy to appear through visual evaluation.
Through the above analysis, the problems and defects of the prior art are as follows: at present, the determination of the laser speckle removing intensity of different color spots depends on more experience, the intensity selection is not accurate enough, the problems of skin burn or incomplete speckle removal are easily caused, and the speckle removing effect is poor. Moreover, the state of the speckles cannot be automatically detected after laser treatment, and the speckles are easy to deviate through visual assessment.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an intelligent laser speckle removing control system and method for dermatology.
The invention is realized in this way, a dermatology intelligent laser speckle removing control system, which comprises:
the image acquisition module is connected with the central control module and is used for acquiring a facial image through an image acquisition program;
the image analysis module is connected with the central control module and is used for analyzing the acquired image through an image analysis program;
the spot removing area delimiting module is connected with the central control module and is used for delimiting a spot removing area according to the spot position and the program determined according to the image analysis result;
the central control module is connected with the image acquisition module, the image analysis module, the spot removing area defining module, the spot position determining module, the spot diameter determining module, the spot information analysis module, the intensity determining module, the cleaning module, the anesthetic coating module, the anesthetic detection module, the laser spot removing module, the cold compress module, the spot detection module and the human-computer interaction module and is used for controlling the normal operation of each module through the main control computer;
the color spot position determining module is connected with the central control module and is used for determining the color spot position according to the image analysis result through a color spot position determining program;
the color spot diameter measuring module is connected with the central control module and is used for determining the color spot diameter according to the image analysis result through a color spot diameter measuring program;
the color spot information analysis module is connected with the central control module and is used for determining the depth information of the color spots by combining a color spot information analysis program with the color spot diameter;
the intensity determination module is connected with the central control module and is used for determining the spot removing intensity according to the diameter and the depth of the spot through an intensity control program;
the cleaning module is connected with the central control module and is used for cleaning and disinfecting the freckle removing area by using clean water and alcohol through a cleaning program;
the anesthetic coating module is connected with the central control module and is used for coating the anesthetic in the freckle removing area through an anesthetic coating program;
the narcotic detection module is connected with the central control module and is used for detecting the narcotic absorption condition of the freckle removing area through a narcotic detection program;
the laser spot removing module is connected with the central control module and is used for removing spots by laser through a laser spot removing instrument;
the cold compress module is connected with the central control module and is used for performing cold compress on the freckle removing area after freckle removal through the cold compress bag;
the color spot detection module is connected with the central control module and is used for detecting the state of the color spots after laser treatment and evaluating the effect of the color spots after treatment;
and the human-computer interaction module is connected with the central control module and used for presetting and inputting working parameters through the touch display screen and displaying the working state of the system in real time.
Another objective of the present invention is to provide a dermatology intelligent laser speckle removing control method, which includes the following steps:
acquiring a facial image by an image acquisition module by using an image acquisition program; analyzing the collected image by an image analysis module by using an image analysis program;
secondly, defining a spot removing area by a spot removing area defining module according to a program determined by the spot position according to an image analysis result; determining the color spot position by a color spot position determining module according to the image analysis result by using a color spot position determining program;
thirdly, determining the color spot diameter by a color spot diameter determination module according to an image analysis result by using a color spot diameter determination program; determining depth information of the color spots by a color spot information analysis module by combining a color spot information analysis program with the color spot diameters;
fourthly, determining the spot removing intensity according to the diameter and the depth of the spot by an intensity control program through an intensity determination module;
step five, cleaning and disinfecting the spot-removing area by using clean water and alcohol through a cleaning module by using a cleaning program;
sixthly, coating the spot-removing area by using an anesthetic coating program through an anesthetic coating module; detecting the drug absorption condition of the freckle removing area by using a drug detection program through a drug detection module;
seventhly, performing laser spot removal on the determined spot position according to preset intensity by using a laser spot removal instrument through a laser spot removal module;
step eight, detecting the color spot state after laser treatment through a color spot state detection module, performing the step nine when detecting that the treatment effect reaches the preset satisfaction degree, and repeating the step seven if the preset satisfaction degree is not reached;
and step nine, performing cold compress on the freckle-removing area after freckle removal by using the cold compress pack through the cold compress module.
Further, in the step one, the analyzing the collected image by the image analyzing module using the image analyzing program includes the steps of:
(1) Acquiring an acquired facial image, and identifying a facial contour to obtain a facial area;
(2) The method comprises the steps of delineating a face area in an acquired image;
(3) Calculating the number of grey scales of the delineated area;
(4) Carrying out scratching treatment on the sketched region by aiming at the acquired image;
(5) And calculating the gray degree of the remaining area after the scratching processing.
Further, in the step (3), the calculating the number of grayscales of the delineated region specifically includes: and detecting the definition of the acquired image, and calculating the color richness and color fluctuation degree in the image.
Further, in the third step, the color spot diameter is determined by the color spot diameter determination module according to the image analysis result by using a color spot diameter determination program, and the specific steps are as follows:
1) Measuring the distance between the laser speckle removing instrument and the face;
2) Acquiring and outputting feature points of the acquired facial image;
3) Selecting at least two feature points from the image of the photographed object based on the output information of the feature points;
4) Calculating a relative size of an original image for the photographic subject based on the measured distance;
5) Extracting feature points in an original image pre-stored for the photographic subject corresponding to the selected at least two feature points on the basis of the calculated relative sizes;
6) And comparing the shot image of the shot object with the original image on the basis of the selected characteristic points and the extracted characteristic points to obtain the color spot diameter.
Further, in step 2), the acquiring and outputting the feature points of the acquired face image specifically includes: and drawing an initial color spot profile curve for a color spot area in the image to obtain a color spot initial area, performing RGB-HSV space transformation processing on the image, replacing an original pixel value with an Euclidean distance between a color vector of each pixel point of the color spot initial area and an average color vector of the color spot initial area, and performing iterative computation on the edge of the color spot initial area through a GVF Snake model.
Further, in the sixth step, when the anesthetic coating module coats the anesthetic on the spot-removing area by using an anesthetic coating program, the coating anesthetic is lidocaine hydrochloride.
Further, in the sixth step, when the anesthetic coating program is used for coating the freckle removing area of the anesthetic by the anesthetic coating module, the coating thickness of the anesthetic is 1-2mm.
Further, in the sixth step, the detecting, by the narcotic detection module, the narcotic absorption condition of the spot-removing area by using the narcotic detection program includes:
step A, local stabbing pain is carried out on an area coated with the anesthetic;
b, detecting the pain of the stabbing pain area by using an anesthesia detector and giving a pain grade;
c, analyzing and obtaining the tolerance of the patient to pain;
d, determining the absorption condition of the anesthetic, wiping off the anesthetic if the absorption is good, and removing the spots; if the absorption is poor, the second dressing is performed.
Further, the analysis obtains the tolerance of the patient to pain, specifically:
extracting a characteristic operator for pain detection in the anesthesia detector, wherein the characteristic operator takes the priority of the characteristic operator in the pain level judgment median sequence as an extraction sequence, and firstly extracting the characteristic operator with high priority; calculating an initial pain grade by using a convolutional neural network algorithm according to the characteristic operator; and judging the difference value between the pain grade and the initial pain grade, and if the absolute value of the difference value is within a preset deviation range, outputting the initial pain grade to obtain the tolerance of the patient to the pain.
Further, in the eighth step, the detecting the color spot state after the laser treatment by the color spot state detecting module specifically includes:
s41, acquiring a processing and analyzing result of the initial color spot image obtained by the image analyzing module in the step one;
s42, collecting the treated color spot image through an image collecting module, and processing and analyzing the collected color spot image;
s43, comparing the treated color spot image after treatment and analysis with the initial image, and evaluating the treatment effect;
and S44, judging whether the treatment effect reaches a preset satisfaction degree parameter according to the evaluation result.
Further, in step S44, the comparing the treated mottle image after treatment and analysis with the initial image to evaluate the treatment effect specifically includes:
s51, extracting parameters of an objective evaluation basis of the image quality of the color spot image;
s52, performing machine learning by using parameters extracted from the standard image sequence in the image library;
s53, fitting the color spot image quality evaluation result with the extracted parameters by using the learning result;
and S54, applying the fitting result to the image to be evaluated, comparing the fitting result with the subjective evaluation score, inputting the comparison result into a support vector machine for continuous learning, and outputting a satisfaction degree parameter.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention realizes the determination of the color spot position by collecting the face image, and the accuracy of removing the color spot is better; the method has the advantages that the method can realize mastering of the color spot information by acquiring the diameter and depth information of the color spot, can conveniently remove the color spots with different intensities, has better pertinence and better effect, can effectively remove the color spot, and does not hurt normal skin; the freckle-removing pain of a patient is reduced by detecting the absorption of the anesthetic, and cold compress is performed after freckle removal, so that the freckle-removing wound is calmed, the freckle-removing comfort level is improved, and the recovery of the patient is better; the red distinguishing value, the a value and the L value of the PWS focus in the middle of the face can be reduced, and the clinical curative effect is satisfactory.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a block diagram of a structure of an intelligent laser speckle removing control system for dermatology provided by an embodiment of the present invention;
in the figure: 1. an image acquisition module; 2. an image analysis module; 3. a spot-removing area delimiting module; 4. a central control module; 5. a color spot position determination module; 6. a color spot diameter measuring module; 7. a color spot information analysis module; 8. an intensity determination module; 9. a cleaning module; 10. an anesthetic coating module; 11. an anesthetic detection module; 12. a laser speckle removing module; 13. a cold compress module; 14. a color spot detection module; 15. and a man-machine interaction module.
Fig. 2 is a flowchart of a dermatological intelligent laser speckle removal control method according to an embodiment of the present invention.
Fig. 3 is a flowchart of analyzing a captured image by an image analysis module using an image analysis program according to an embodiment of the present invention.
Fig. 4 is a flowchart of determining the stain diameter according to the image analysis result by the stain diameter determination module using the stain diameter determination program according to the embodiment of the present invention.
Fig. 5 is a flowchart of detecting an anesthetic absorption condition of the speckle removing area by an anesthetic detection module using an anesthetic detection program according to an embodiment of the present invention.
Fig. 6 is a flowchart of a detection method of the color spot status detection module according to an embodiment of the present invention.
Fig. 7 is a flow chart of a method for evaluating the effect of a treatment according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
Aiming at the problems in the prior art, the invention provides an intelligent laser speckle removing control system and a control method for dermatology, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the intelligent laser speckle removing control system for dermatology provided by the embodiment of the present invention includes:
the image acquisition module 1 is connected with the central control module 4 and is used for acquiring a facial image through an image acquisition program;
the image analysis module 2 is connected with the central control module 4 and is used for analyzing the acquired image through an image analysis program;
the spot removing area delimiting module 3 is connected with the central control module 4 and is used for delimiting a spot removing area according to the spot position and the program determined according to the image analysis result;
the central control module 4 is connected with the image acquisition module 1, the image analysis module 2, the spot removing area defining module 3, the spot position determining module 5, the spot diameter measuring module 6, the spot information analysis module 7, the intensity determining module 8, the cleaning module 9, the anesthetic coating module 10, the anesthetic detection module 11, the laser spot removing module 12, the cold compress module 13, the spot detection module 14 and the human-computer interaction module 15, and is used for controlling the normal operation of each module through a main control computer;
the color spot position determining module 5 is connected with the central control module 4 and used for determining the color spot position according to the image analysis result through a color spot position determining program;
the color spot diameter measuring module 6 is connected with the central control module 4 and is used for determining the color spot diameter according to the image analysis result through a color spot diameter measuring program;
the color spot information analysis module 7 is connected with the central control module 4 and is used for determining the depth information of the color spots by combining a color spot information analysis program with the color spot diameter;
the intensity determination module 8 is connected with the central control module 4 and is used for determining the spot removing intensity according to the diameter and the depth of the spot through an intensity control program;
the cleaning module 9 is connected with the central control module 4 and is used for cleaning and disinfecting the freckle removing area by using clean water and alcohol through a cleaning program;
the anesthetic coating module 10 is connected with the central control module 4 and is used for coating the anesthetic on the freckle removing area through an anesthetic coating program;
the anesthetic detection module 11 is connected with the central control module 4 and used for detecting the anesthetic absorption condition of the freckle removing area through an anesthetic detection program;
the laser spot removing module 12 is connected with the central control module 4 and is used for removing spots by laser through a laser spot removing instrument;
the cold compress module 13 is connected with the central control module 4 and is used for performing cold compress on the spot-removing area after spot removal through the cold compress bag;
the color spot detection module 14 is connected with the central control module and is used for detecting the state of the color spots after laser treatment and evaluating the effect of the color spots after treatment;
and the human-computer interaction module 15 is connected with the central control module and is used for presetting and inputting working parameters through the touch display screen and displaying the working state of the system in real time.
As shown in fig. 2, the dermatological intelligent laser speckle removing control method provided by the embodiment of the invention comprises the following steps:
s101, acquiring a facial image by an image acquisition module by using an image acquisition program; analyzing the collected image by an image analysis module by using an image analysis program;
s102, determining a program to divide a spot-removing area according to an image analysis result by using a spot-removing area dividing module; determining the color spot position according to the image analysis result by a color spot position determination module by using a color spot position determination program;
s103, determining the color spot diameter according to the image analysis result by using a color spot diameter determination program through a color spot diameter determination module; determining depth information of the color spot by combining a color spot information analysis program and a color spot diameter through a color spot information analysis module;
s104, determining the spot removing intensity according to the diameter and the depth of the spot by an intensity determination module and an intensity control program;
s105, cleaning and disinfecting the freckle removing area by using clean water and alcohol through a cleaning module by using a cleaning program;
s106, coating the spot-removing area with the anesthetic by using an anesthetic coating program through an anesthetic coating module; detecting the drug absorption condition of the freckle removing area by using a drug detection program through a drug detection module;
s107, performing laser spot removal on the determined spot position according to preset intensity by using a laser spot removal instrument through a laser spot removal module;
s108, detecting the color spot state after laser treatment by using the color spot state detection module, performing step S109 when detecting that the treatment effect reaches a preset satisfaction degree, and repeating step S107 if the treatment effect does not reach the preset satisfaction degree;
and S109, performing cold compress on the spot-removing area after spot removal by using the cold compress pack through the cold compress module.
As shown in fig. 3, in step S101, the analyzing of the collected image by the image analysis module using the image analysis program according to the embodiment of the present invention includes the following steps:
s201, acquiring a collected face image, and identifying a face contour to obtain a face area;
s202, delineating a face region in the acquired image;
s203, calculating the gray scale number of the delineated region;
s204, carrying out scratching processing on the drawn region aiming at the acquired image;
and S205, calculating the number of gray scales of the remaining area after the matting processing.
In step S203, the calculation of the number of grayscales of the delineated region provided by the embodiment of the present invention specifically includes: and detecting the definition of the acquired image, and calculating the color richness and color fluctuation degree in the image.
As shown in fig. 4, in step S103, the color spot diameter determination module determines the color spot diameter according to the image analysis result by using the color spot diameter determination program according to the embodiment of the present invention, specifically:
s301, measuring the distance between the laser speckle removing instrument and the face;
s302, acquiring and outputting feature points of the acquired facial image;
s303, selecting at least two feature points from the image of the captured subject based on the output information of the feature points;
s304, calculating the relative size of the original image of the shooting object based on the measured distance;
s305, extracting feature points in an original image pre-stored for the photographic subject corresponding to the selected at least two feature points based on the calculated relative size;
s306, comparing the shot image of the shot object with the original image based on the selected characteristic points and the extracted characteristic points to obtain the color spot diameter.
In step S302, the acquiring and outputting feature points of the acquired facial image provided by the embodiment of the present invention specifically includes: and sketching an initial color spot profile curve for a color spot area in the image to obtain a color spot initial area, carrying out RGB-HSV (red, green and blue) -space transformation processing on the image, replacing an original pixel value with an Euclidean distance between a color vector of each pixel point of the color spot initial area and an average color vector of the color spot initial area, and carrying out iterative computation on the edge of the color spot initial area through a GVF Snake model.
In step S106, when the anesthetic coating module according to the embodiment of the present invention coats the anesthetic on the spot-removed area by using the anesthetic coating program, the coating anesthetic is lidocaine hydrochloride.
In step S106, when the anesthetic coating module according to the embodiment of the present invention coats the anesthetic on the spot-removing area by using the anesthetic coating program, the anesthetic coating thickness is 1 to 2mm.
As shown in fig. 5, in step S106, the detecting, by the anesthesia detection module, an anesthesia absorption condition of the speckle removing area by using an anesthesia detection program according to the embodiment of the present invention includes:
s401, local stabbing pain is carried out on the area coated with the anesthetic;
s402, detecting the pain sense of the stabbing pain area by using an anesthesia detector and giving a pain sense grade;
s403, analyzing and obtaining the tolerance of the patient to pain;
s404, determining the absorption condition of the anesthetic, wiping off the anesthetic if the absorption is good, and removing the spots; if the absorption is poor, the second dressing is performed.
In step S403, the analysis provided in the embodiment of the present invention obtains the tolerance of the patient to pain, which specifically includes:
extracting a characteristic operator for pain detection in the anesthesia detector, wherein the characteristic operator takes the priority of the characteristic operator in the pain level judgment median sequence as an extraction sequence, and firstly extracting the characteristic operator with high priority; calculating an initial pain grade by using a convolutional neural network algorithm according to the characteristic operator; and judging the difference value between the pain grade and the initial pain grade, and if the absolute value of the difference value is within a preset deviation range, outputting the initial pain grade to obtain the tolerance of the patient to the pain.
As shown in fig. 6, in step S108 in the embodiment of the present invention, the detecting the color spot state after the laser treatment by the color spot state detecting module specifically includes:
s501, acquiring a processing and analyzing result of the initial color spot image obtained by the image analyzing module in the first step;
s502, collecting the treated color spot image through an image collecting module, and processing and analyzing the collected color spot image;
s503, comparing the treated and analyzed color spot image with the initial image, and evaluating the treatment effect;
and S504, judging whether the treatment effect reaches a preset satisfaction degree parameter according to the evaluation result.
As shown in fig. 7, in step S504 in the embodiment of the present invention, the comparing the treated mottle image after being processed and analyzed with the initial image, and evaluating the treatment effect specifically includes:
s601, extracting parameters of an objective evaluation basis of image quality of the color spot image;
s602, performing machine learning by using parameters extracted from a standard image sequence in an image library;
s603, fitting the color spot image quality evaluation result with the extracted parameters by using the learning result;
and S604, applying the fitting result to the image to be evaluated, comparing the fitting result with the subjective evaluation score, inputting the comparison result into a support vector machine for continuous learning, and outputting a satisfaction degree parameter.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention should not be limited thereto, and any modifications, equivalents and improvements made by those skilled in the art within the technical scope of the present invention as disclosed in the present invention should be covered thereby.

Claims (7)

1. The dermatology department intelligent laser speckle removing control system is characterized by comprising:
the image acquisition module is connected with the central control module and is used for acquiring a facial image through an image acquisition program;
the image analysis module is connected with the central control module and is used for analyzing the acquired image through an image analysis program;
the spot removing area dividing module is connected with the central control module and used for determining a program to divide a spot removing area according to the image analysis result through the spot position;
the central control module is connected with the image acquisition module, the image analysis module, the spot removing area defining module, the spot position determining module, the spot diameter determining module, the spot information analysis module, the intensity determining module, the cleaning module, the anesthetic coating module, the anesthetic detection module, the laser spot removing module, the cold compress module, the spot detection module and the human-computer interaction module and is used for controlling the normal operation of each module through the main control computer;
the color spot position determining module is connected with the central control module and is used for determining the color spot position according to the image analysis result through a color spot position determining program;
the color spot diameter measuring module is connected with the central control module and is used for determining the color spot diameter through a color spot diameter measuring program according to an image analysis result;
the color spot information analysis module is connected with the central control module and is used for determining the depth information of the color spots by combining a color spot information analysis program with the color spot diameter;
the intensity determination module is connected with the central control module and is used for determining the spot removing intensity according to the diameter and the depth of the spot through an intensity control program;
the cleaning module is connected with the central control module and is used for cleaning and disinfecting the freckle removing area by using clean water and alcohol through a cleaning program;
the anesthetic coating module is connected with the central control module and is used for coating the anesthetic in the freckle removing area through an anesthetic coating program;
the narcotic detection module is connected with the central control module and is used for detecting the narcotic absorption condition of the freckle removing area through a narcotic detection program;
the laser spot removing module is connected with the central control module and is used for removing spots by laser through a laser spot removing instrument;
the cold compress module is connected with the central control module and is used for performing cold compress on the spot-removing area after spot removal through the cold compress bag;
the color spot detection module is connected with the central control module and is used for detecting the state of the color spots after laser treatment and evaluating the effect of the color spots after treatment;
the man-machine interaction module is connected with the central control module and used for presetting and inputting working parameters through the touch display screen and displaying the working state of the system in real time;
the dermatological intelligent laser speckle removing control system executes the following steps:
firstly, acquiring a facial image by an image acquisition module by using an image acquisition program; analyzing the collected image by an image analysis module by using an image analysis program;
the analysis of the collected image by the image analysis module by using an image analysis program comprises the following steps:
s11, acquiring an acquired facial image, and identifying a facial contour to obtain a facial area;
s12, sketching a face area in the acquired image;
s13, calculating the number of grey scales of the delineated area;
s14, carrying out scratching treatment on the sketched regions by aiming at the acquired images;
s15, calculating the gray scale number of the remaining area after the cutting processing;
secondly, defining a spot removing area by a spot removing area defining module according to a program determined by the spot position according to an image analysis result; determining the color spot position by a color spot position determining module according to the image analysis result by using a color spot position determining program;
thirdly, determining the color spot diameter by a color spot diameter determination module according to an image analysis result by using a color spot diameter determination program; determining depth information of the color spot by combining a color spot information analysis program and a color spot diameter through a color spot information analysis module;
fourthly, determining the spot removing intensity according to the diameter and the depth of the spot by an intensity control program through an intensity determination module;
step five, cleaning and disinfecting the spot-removing area by using clean water and alcohol through a cleaning module by using a cleaning program;
sixthly, coating the spot-removing area by using an anesthetic coating program through an anesthetic coating module; detecting the drug absorption condition of the freckle removing area by using a drug detection program through a drug detection module;
seventhly, performing laser spot removal on the determined spot position according to preset intensity by using a laser spot removal instrument through a laser spot removal module;
step eight, detecting the color spot state after laser treatment through a color spot state detection module, performing the step nine when the detection result reaches the preset satisfaction degree, and repeating the step seven if the preset satisfaction degree is not reached;
step nine, performing cold compress on the spot-removing area after spot removal by using a cold compress pack through a cold compress module;
the color spot diameter is determined by a color spot diameter determination module according to an image analysis result by using a color spot diameter determination program, and the color spot diameter determination method specifically comprises the following steps:
s21, measuring the distance between the laser freckle removing instrument and the face;
s22, acquiring and outputting the feature points of the acquired facial image;
s23, selecting at least two feature points from the image of the subject to be photographed based on the outputted information of the feature points;
s24, calculating the relative size of the original image of the shooting object based on the measured distance;
s25, extracting feature points in an original image prestored for the photographic subject corresponding to the selected at least two feature points on the basis of the calculated relative size;
s26, comparing the shot image of the shot object with the original image based on the selected characteristic points and the extracted characteristic points to obtain color spot diameters;
the method for acquiring and outputting the feature points of the acquired facial image specifically comprises the following steps: and sketching an initial color spot profile curve for a color spot area in the image to obtain a color spot initial area, carrying out RGB-HSV (red, green and blue) -space transformation processing on the image, replacing an original pixel value with an Euclidean distance between a color vector of each pixel point of the color spot initial area and an average color vector of the color spot initial area, and carrying out iterative computation on the edge of the color spot initial area through a GVF Snake model.
2. The dermatologic intelligent laser speckle removing control system of claim 1, wherein in the sixth step, when the speckle removing region anesthetic is coated by the anesthetic coating module by using an anesthetic coating program, the coated anesthetic is lidocaine hydrochloride.
3. The dermatologic intelligent laser speckle removing control system of claim 1, wherein in the sixth step, when the speckle removing area is coated with the anesthetic by the anesthetic coating module by using an anesthetic coating program, the coating thickness of the anesthetic is 1-2mm.
4. The dermatologic intelligent laser speckle removing control system of claim 1, wherein in step six, the detecting, by the speckle detecting module, the absorption of the anesthetic in the speckle removing area by the anesthetic detecting program includes:
s31, local stabbing pain is carried out on the area coated with the anesthetic;
s32, detecting the pain sense of the stabbing pain area by using an anesthesia detector and giving a pain sense grade;
s33, analyzing and obtaining the tolerance of the patient to pain;
and S34, determining the absorption condition of the anesthetic, and removing freckles.
5. The dermatologic intelligent laser speckle removal control system of claim 4, wherein the analysis obtains the tolerance of the patient to pain, specifically:
extracting a characteristic operator for pain detection in the anesthesia detector, wherein the characteristic operator takes the priority of the characteristic operator in the pain grade judgment median order as an extraction sequence, and firstly extracts the characteristic operator with high priority; calculating an initial pain grade by using a convolutional neural network algorithm according to the characteristic operator; and judging the difference value between the pain grade and the initial pain grade, and if the absolute value of the difference value is within a preset deviation range, outputting the initial pain grade to obtain the tolerance of the patient to the pain.
6. The dermatologic intelligent laser speckle removing control system of claim 1, wherein in the step eight, the detecting the state of the speckles after the laser treatment by the speckle state detecting module specifically comprises:
s41, acquiring a processing and analyzing result of the initial color spot image obtained by the image analyzing module in the step one;
s42, collecting the treated color spot image through an image collecting module, and processing and analyzing the collected color spot image;
s43, comparing the treated and analyzed color spot image with the initial image, and evaluating the treatment effect;
and S44, judging whether the treatment effect reaches a preset satisfaction degree parameter according to the evaluation result.
7. The dermatologic intelligent laser speckle removing control system of claim 6, wherein in step S44, the comparing the processed and analyzed treated speckle image with the initial image to evaluate the treatment effect specifically comprises:
s51, extracting parameters of an objective evaluation basis of the image quality of the color spot image;
s52, performing machine learning by using parameters extracted from the standard image sequence in the image library;
s53, fitting the color spot image quality evaluation result with the extracted parameters by using the learning result;
and S54, applying the fitting result to the image to be evaluated, comparing the fitting result with the subjective evaluation score, inputting the comparison result into a support vector machine for continuous learning, and outputting a satisfaction degree parameter.
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