Medical mid-infrared 1720nm pulse fiber laser

Abstract

The invention discloses a medical mid-infrared 1720 nm pulse fiber laser, which relates to the technical field of laser medicine, and comprises the following steps: collecting data of the pulse fiber laser, respectively calculating a thulium-doped ion concentration uniformity index, laser energy intensity and ablation indexes of small target tissue ablation areas, and calculating a thulium-doped ion concentration uniformity index and a thulium-doped ion concentration uniformity index, a thulium-doped ion concentration uniformity index and a thulium-doped ion concentration uniformity index; according to the method, the spectrum analysis technology, the multiple linear regression algorithm, the convolutional neural network algorithm and the modern information technology are closely combined, the multiple thulium-doped optical fiber sections are combined, and the anti-fake color coding graph of the target tissue ablation area is drawn. The thulium-doped ion concentration distribution uniformity degree and the target tissue ablation degree are comprehensively monitored in real time, monitored data become more accurate indexes under the same condition, and the intelligent degree of the medical intermediate infrared 1720n pulse fiber laser in the using process is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of laser medicine, in particular to a medical mid-infrared 1720nm pulsed fiber laser. Background Art

[0002] Traditional mid-infrared laser light sources have problems such as large size, low efficiency and complex maintenance, which make it difficult to meet the modern medical needs for miniaturization, portability and high stability of equipment. Fiber lasers, with their advantages of flexible transmission, high beam quality, high efficiency and easy integration, have become an ideal choice for the new generation of medical lasers. In the medical field, the application of laser technology is becoming more and more extensive, and the demand for lasers with specific wavelengths and pulse characteristics continues to grow. Mid-infrared band lasers have shown great potential in medical surgery and treatment due to their strong absorption characteristics with water molecules in biological tissues. Lasers with a wavelength of 1720nm are in the golden window of the mid-infrared band, and water molecules have a high absorption coefficient for them, which can achieve precise tissue cutting and hemostasis. They are of great application value in surgical scenarios such as urology prostate surgery and dermatology plastic surgery. Therefore, the development of 1720nm pulsed fiber lasers based on thulium-doped fiber has broken through key technical limitations and is of great significance to promoting the innovation and development of medical laser equipment.

[0003] Traditional medical mid-infrared pulsed fiber lasers often use thulium-doped fiber as the gain medium. However, there is a problem of uneven distribution of thulium-doped fiber ion concentration, which leads to a gain saturation effect and reduces the laser conversion efficiency. In addition, when the medical mid-infrared pulsed fiber laser acts on the target tissue, it is difficult to analyze the nonlinear relationship between laser energy intensity and the degree of tissue ablation, resulting in a lack of accurate monitoring of the damage to the target tissue. Therefore, how to combine and analyze the gain medium spectral data, pulsed fiber temperature data, laser data and target tissue data to solve the problems existing in traditional medical mid-infrared pulsed fiber lasers is the problem to be solved by the present invention. Therefore, a medical mid-infrared 1720nm pulsed fiber laser is proposed. Summary of the Invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: A medical mid-infrared 1720nm pulsed fiber laser, comprising the following steps:

[0005] Step 1: Collect pulsed fiber laser data. The pulsed fiber laser data includes thulium-doped fiber spectrum data, pulsed fiber data, laser data, and target tissue data, providing a data foundation for the implementation of subsequent steps.

[0006] Step 2: Extract features from the thulium-doped fiber spectrum data and combine it with the pulse fiber data to obtain the thulium-doped fiber ion concentration distribution evaluation data, and normalize it to eliminate dimensionality problems in subsequent calculations. Then, calculate the thulium-doped ion concentration uniformity index and evaluate the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped fiber segment;

[0007] Step 3: Using laser data, calculate the laser output wavelength accuracy. Combined with the pulsed fiber temperature data and a multivariate linear regression algorithm, a laser energy intensity output model is constructed to obtain the corresponding laser energy intensity. Using the target tissue data, the ablation index of each small target tissue ablation area is calculated, the ablation degree of each small target tissue ablation area is analyzed, and the ablation degree of each small target tissue ablation area is numbered.

[0008] Step 4: construct a heat map matrix of each small thulium-doped fiber segment based on the uniformity of the distribution of thulium ion concentration in each small thulium-doped fiber segment; and draw an anti-counterfeiting color-coded map of each small target tissue ablation area based on the degree of ablation in each small target tissue ablation area;

[0009] Step 5: Combine the laser energy intensity, the ablation degree number of each small target tissue ablation area, and the convolutional neural network algorithm to construct a target tissue damage analysis model;

[0010] Step six, based on the thermal map matrix of each small thulium-doped fiber segment and the anti-counterfeiting color coding map of each target tissue ablation area, analyze the uniformity of the distribution of thulium-doped ion concentration in each small thulium-doped fiber segment and the ablation degree of each small target tissue ablation area respectively, and based on the number of each small thulium-doped fiber segment and the number of each small target tissue ablation area, locate each small thulium-doped fiber segment corresponding to the abnormal uniformity of thulium-doped ion concentration distribution and each target tissue ablation area corresponding to the abnormal ablation degree, and take corresponding measures to improve the problems of abnormal uniformity of thulium-doped ion concentration distribution and abnormal ablation degree.

[0011] A further improvement of the technical solution of the present invention is that, in step 1, the process of collecting pulsed fiber laser data includes:

[0012] Divide the thulium-doped optical fiber into several segments to obtain each small thulium-doped optical fiber segment, and divide the target tissue ablation area into several areas of equal area to obtain each small target tissue ablation area;

[0013] Deploy different types of acquisition equipment to collect thulium-doped fiber spectral data, pulsed fiber data, laser data, and target tissue data. These different types of acquisition equipment include broadband light sources, optical spectrum analyzers, laser pump sources, tunable lasers, optical power meters, distributed fiber temperature measurement systems, optical time-domain reflectometers, wavelength meters, spot analyzers, high-speed photodetectors, oscilloscopes, photoacoustic imaging systems, backscattered light diagnostic systems, optical coherence tomography systems, and fiber Bragg grating temperature monitoring systems.

[0014] Thulium-doped fiber spectral data includes the absorption spectrum, fluorescence spectrum, and gain spectrum of trivalent thulium ions in the thulium-doped fiber; pulse fiber data includes the temperature and length of each section of the pulse fiber; laser data includes the actual output laser wavelength of the laser, the spot diameter when the laser beam acts on the tissue surface, and the pulse frequency of the laser pulse sequence; target tissue data includes the photoacoustic signal intensity, backscattered light intensity, thermal damage depth, and temperature of the ablation area of ​​the target tissue when the laser is applied;

[0015] The above-mentioned pulse optical fiber includes thulium-doped optical fiber and other types of optical fibers. The main type of pulse optical fiber used in the realization of the function of a medical mid-infrared 1720nm pulsed fiber laser in the present invention is thulium-doped optical fiber. Therefore, the uniformity of the thulium-doped optical fiber ion concentration distribution can be evaluated by analyzing the evaluation data of the thulium-doped optical fiber ion concentration distribution.

[0016] The pulse fiber data, laser data and target tissue data are cleaned and normalized, and the thulium-doped fiber spectrum data are subjected to baseline correction, wavelength calibration and spectrum smoothing. The baseline correction is used to eliminate the interference of the fiber matrix material, detector noise or ambient light; the wavelength calibration is used to correct the wavelength accuracy error of the spectrometer; the spectrum smoothing is used to reduce high-frequency noise and highlight the characteristic peaks. Timestamps are assigned to each type of preprocessed pulse fiber laser data, and the assigned timestamps are adjusted to achieve synchronization of the acquisition time of the thulium-doped fiber spectrum data, pulse fiber data, laser data and target tissue data. The thulium-doped fiber spectrum data, pulse fiber data, laser data and target tissue data are integrated to generate a pulse fiber laser data set.

[0017] A further improvement of the technical solution of the present invention is that in step 2, the process of obtaining the thulium-doped fiber ion concentration distribution evaluation data by feature extraction and normalizing it includes:

[0018] The evaluation data of thulium-doped fiber ion concentration distribution include the absorption coefficient, gain coefficient and gain saturation threshold power of each small thulium-doped fiber segment, as well as the peak wavelength and full width at half maximum of the fluorescence spectrum corresponding to each small thulium-doped fiber segment;

[0019] A characteristic peak detection algorithm is used to identify the characteristic absorption peak wavelength of trivalent thulium ions from the absorption spectrum of trivalent thulium ions in thulium-doped optical fiber. Based on the theory of rare earth ion spectrum, the energy level transition corresponding to the characteristic absorption peak of trivalent thulium ions is determined. The absorbance is read at the characteristic absorption peak wavelength of trivalent thulium ions. Based on the Lambert-Beer law and the length of each pulse optical fiber segment, the absorption coefficient of each small thulium-doped optical fiber segment is calculated.

[0020] Using spectral analysis technology, the fluorescence intensity and wavelength are extracted from the fluorescence spectrum of trivalent thulium ions in thulium-doped optical fiber. Combined with the derivative method, the peak position of the fluorescence spectrum is determined, and then the corresponding peak wavelength is determined. Based on the peak wavelength of the fluorescence spectrum, the two fluorescence wavelengths corresponding to half the fluorescence intensity are extracted. The absolute value of the difference between the two extracted fluorescence wavelengths is used to calculate the half-maximum full width of the fluorescence spectrum corresponding to each small thulium-doped optical fiber segment.

[0021] Combining the signal gain linear fitting method and the saturation curve nonlinear fitting method, the gain coefficient and gain saturation threshold power of each small thulium-doped fiber segment are extracted from the gain spectrum of trivalent thulium ions in the thulium-doped fiber.

[0022] The absorption coefficient, gain coefficient and gain saturation threshold power of each small thulium-doped fiber segment extracted from the features, as well as the peak wavelength and half-maximum full width of the fluorescence spectrum corresponding to each small thulium-doped fiber segment are subjected to Z-score normalization processing.

[0023] A further improvement of the technical solution of the present invention is that in step 2, the process of calculating the thulium-doped ion concentration uniformity index and evaluating the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped optical fiber segment includes:

[0024] The weighted average dispersion method is used to calculate the thulium-doped fiber ion concentration uniformity index by combining the Z-score normalized thulium-doped fiber ion concentration distribution evaluation data.

[0025] When the thulium-doped ion concentration uniformity index is lower than 0.25, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a low distribution uniformity; when the thulium-doped ion concentration uniformity index is between 0.25 and 0.45, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a medium distribution uniformity; when the thulium-doped ion concentration uniformity index is higher than 0.45, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a high distribution uniformity.

[0026] A further improvement of the technical solution of the present invention is that in step 3, the process of calculating the laser output wavelength accuracy, combining the multivariate linear regression algorithm, and constructing a laser energy intensity output model to obtain the corresponding laser energy intensity includes:

[0027] The target output laser wavelength of the laser was set to 1720 nm. The laser output wavelength accuracy was calculated using the absolute value of the difference between the actual laser output wavelength and the target output laser wavelength. The laser output wavelength accuracy was normalized using the Z-score and then integrated into the pulsed fiber laser dataset.

[0028] The temperature of each pulse fiber segment, the spot diameter of the laser beam when it impacts the tissue surface, the pulse frequency of the laser pulse sequence, and the accuracy of the laser output wavelength were extracted from the pulse fiber laser data set. The extracted data were divided into a first training set and a first test set in an 8:2 ratio.

[0029] Using the first training set data and combining it with a multivariate linear regression algorithm, the first training set data is used as input and the laser energy intensity is used as output. The linear relationship between the temperature of each segment of the pulsed optical fiber, the spot diameter when the laser beam acts on the tissue surface, the pulse frequency of the laser pulse sequence, the laser output wavelength accuracy and the laser energy intensity is learned to train a laser energy intensity output model.

[0030] Inputting the first test set data into the laser energy intensity output model, adjusting the regression coefficient and intercept term of the laser energy intensity output model, optimizing the performance of the laser energy intensity output model, and obtaining the laser energy intensity output model;

[0031] Combined with the current temperature of each section of pulsed optical fiber, the spot diameter when the laser beam acts on the tissue surface, the pulse frequency of the laser pulse sequence and the accuracy of the laser output wavelength, the corresponding laser energy intensity is output and integrated into the pulsed fiber laser data set.

[0032] A further improvement of the technical solution of the present invention is that in step 3, the process of calculating the ablation index of each small target tissue ablation area, analyzing the ablation degree of each small target tissue ablation area, and numbering the ablation degree of each small target tissue ablation area includes:

[0033] The principle of collaboratively evaluating the ablation degree of each small target tissue ablation area based on the target tissue data can be understood as follows: the intensity of the photoacoustic signal when the ablation area of ​​the target tissue is exposed to laser action reflects the energy absorption efficiency and is the prerequisite for ablation; the intensity of the backscattered light when the ablation area of ​​the target tissue is exposed to laser action reflects the degree of tissue structure damage; the depth of the thermal damage when the ablation area of ​​the target tissue is exposed to laser action reflects the ablation range; the temperature of the ablation area of ​​the target tissue when exposed to laser action reflects the intensity of the thermal effect. The ablation index of each small target tissue ablation area is calculated using the preprocessed target tissue data in combination with the nonlinear product model formula. The calculation process is as follows:

[0034]

[0035] Among them, AQ i The ablation index of each small target tissue ablation area, and are the normalized photoacoustic signal intensity, backscattered light intensity, thermal damage depth, and temperature of the ablation area of ​​the target tissue when it is acted upon by the laser, and i is the number of ablation areas of each small target tissue;

[0036] When the ablation index of each small target tissue ablation area is lower than 0.35, it corresponds to a low degree of ablation; when the ablation index of each small target tissue ablation area is between 0.35 and 0.7, it corresponds to a medium degree of ablation; when the ablation index of each small target tissue ablation area is higher than 0.7, it corresponds to a high degree of ablation;

[0037] Numbering the ablation degree of each small target tissue ablation area, and integrating the ablation degree and number of each small target tissue ablation area into the pulsed fiber laser data set;

[0038] A further improvement of the technical solution of the present invention is that, in step 4, the process of constructing the thermal map matrix of each small thulium-doped fiber segment includes:

[0039] Number each small thulium-doped fiber segment, determine the heat map matrix structure, set the row dimension to the number of each small thulium-doped fiber segment, arrange them in ascending order of the number of each small thulium-doped fiber segment, and set the column dimension to the distribution uniformity of the thulium ion concentration in each small thulium-doped fiber segment;

[0040] According to the color mapping rules, continuous color scales are used to represent the high distribution uniformity, medium distribution uniformity and low distribution uniformity of the thulium ion concentration in each small thulium-doped fiber segment from light to dark, and a heat map matrix of each small thulium-doped fiber segment is constructed;

[0041] The explanation of the heat map matrix is: the heat map matrix of each small thulium-doped fiber segment is used to display the distribution uniformity of the thulium-doped fiber concentration in each small thulium-doped fiber segment and its corresponding number. The corresponding small thulium-doped fiber segment can be retrieved according to the number. When subsequent measures are taken, only the small thulium-doped fiber segment corresponding to the number is required, which reduces cost and resources and also realizes the positioning of each small thulium-doped fiber segment corresponding to the abnormal distribution uniformity of the thulium-doped fiber concentration.

[0042] A further improvement of the technical solution of the present invention is that, in step 4, the process of drawing the anti-counterfeiting color-coded map of each target tissue ablation area includes:

[0043] Using color coding technology, green, yellow, and red were selected, and the printed colors were calibrated using Pantone color charts to ensure color accuracy. Green, yellow, and red were associated with low, medium, and high ablation levels in each small target tissue ablation area, respectively.

[0044] Combined with the numbering and labeling technology, each small target tissue ablation area is labeled according to its number, and each small target tissue ablation area is arranged in the order of number using vector graphics software;

[0045] The printing accuracy needs to be adjusted to above 300dpi to ensure that the micron-level texture is clearly discernible, as distortion is prone to occur during copying, and then an anti-counterfeiting color-coded map of each target tissue ablation area is drawn.

[0046] A further improvement of the technical solution of the present invention is that, in step 5, the process of constructing the target tissue damage analytical model includes:

[0047] Extracting the laser energy intensity and the ablation degree number of each small target tissue ablation area from the pulsed fiber laser data set, and dividing the currently extracted data into a second training set and a second test set, with the ratio of the second training set to the second test set being 7:3;

[0048] Combining the second training set data with a convolutional neural network algorithm, the laser energy intensity is used as input and the ablation degree number of each small target tissue ablation area is used as output. The nonlinear relationship between the laser energy intensity and the ablation degree number of each small target tissue ablation area is learned to train the target tissue damage analysis model.

[0049] Inputting the second test set data into the target tissue damage analytical model, comparing the output of the target tissue damage analytical model with the ablation degree number of each actual small target tissue ablation area, evaluating the performance of the target tissue damage analytical model, adjusting the parameters of the target tissue damage analytical model, optimizing the target tissue damage analytical model, and thus obtaining the final target tissue damage analytical model;

[0050] Through the target tissue damage analysis model, the nonlinear relationship between the laser energy intensity and the ablation degree number of each small target tissue ablation area is obtained. By continuously adjusting the target tissue damage analysis model parameters, the accuracy of the target tissue damage analysis model output results is improved. In the subsequent monitoring of the ablation degree of each small target tissue ablation area, the precise ablation degree of each small target tissue ablation area can be obtained by analyzing the laser energy intensity, and then the anti-counterfeiting color coding map of each target tissue ablation area is updated, saving the monitoring cost.

[0051] A further improvement of the technical solution of the present invention is that, in step 6, the process of evaluating each target tissue ablation area corresponding to abnormal thulium ion concentration uniformity distribution and abnormal ablation degree and taking corresponding measures to improve the process includes:

[0052] Analyze the thermal map matrix of each small thulium-doped fiber segment, and obtain the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped fiber segment according to the color depth of the continuous color scale. Retrieve the corresponding small thulium-doped fiber segment number based on the row dimension. When the thulium-doped ion concentration in the small thulium-doped fiber segment is highly uniform, it indicates that the thulium-doped ions are uniformly distributed in the fiber core layer without concentration gradient, the pump light absorption efficiency is high and uniform, and the laser mode is stable. The existing fiber manufacturing process of the corresponding small thulium-doped fiber segment is retained to ensure the stability of the doping uniformity. A pump source matching the fiber absorption peak is used to maximize the energy coupling efficiency. It can be used for high-precision surgery and the stable laser output brought by high uniformity can achieve the advantages of clear tissue ablation boundaries and small thermal damage. When the thulium-doped ion concentration in the small thulium-doped fiber segment is moderately uniform, it indicates that there are slight local concentration fluctuations of the thulium-doped ions, which may cause local overheating or mode instability. The inner cladding gradient refractive index design is adopted to compensate for the pump light absorption unevenness caused by the ion concentration gradient by adjusting the inner cladding diameter or doping distribution, optimize the heat conduction efficiency of the clamping structure of the corresponding small thulium-doped fiber segment, and promptly remove the heat generated by local hot spots to avoid the glass matrix from cracking due to thermal stress. The pulse width modulation technology is used to shorten the high-power pulse duration in the corresponding small thulium-doped fiber segment and reduce the heat accumulation effect. When the thulium-doped ion concentration in the small thulium-doped fiber segment is of low distribution uniformity, it indicates that the thulium-doped ion concentration presents significant spatial inhomogeneity, which may cause serious mode distortion, power hopping or fiber damage. Unqualified small thulium-doped fiber segments are eliminated, and the segmented pumping technology is adopted to set an independent pump source in the corresponding small thulium-doped fiber segment. The pump energy of each segment is dynamically adjusted according to the concentration distribution. The chirped pulse amplification technology is introduced to broaden, amplify and compress the pulse sequence, reduce the peak power density, and avoid nonlinear effects such as self-phase modulation and four-wave mixing.

[0053] According to the color of each small target tissue ablation area in the anti-counterfeiting color coding map of each target tissue ablation area, analyze the ablation degree of each small target tissue ablation area, and retrieve the number corresponding to each small target tissue ablation area according to the number label. When the small target tissue ablation area is green, it corresponds to a low ablation degree, indicating that the corresponding small target tissue ablation area has only slight thermal damage and has not reached the coagulation or vaporization threshold. The ablation plan of the corresponding small target tissue ablation area is maintained; when the small target tissue ablation area is yellow, it corresponds to a medium ablation degree, indicating that the corresponding small target tissue ablation area has coagulative necrosis and there is a reversible thermal damage zone at the edge. , intermittent irradiation is used, and thermal relaxation time is used to reduce the damage to the ablation area of ​​small target tissue with normal peripheral ablation degree. Single-point irradiation is changed to spiral scanning and fence scanning to evenly cover the corresponding small target tissue ablation area and reduce local excessive ablation; when the ablation area of ​​small target tissue is red, it corresponds to a high degree of ablation, indicating that the tissue is vaporized, carbonized or even perforated, and there is irreversible thermal damage at the edge, which may be accompanied by the risk of bleeding and perforation. Use saline spray and low-temperature gas to cool the corresponding small target tissue ablation area to below 37°C, reduce the expansion of the carbonization range, and combine laser with other energy forms to complement the ablation needs.

[0054] The beneficial effects of the present invention are as follows: compared with the traditional medical mid-infrared pulsed fiber laser, the spectral analysis technology, multivariate linear regression algorithm and convolutional neural network algorithm in the method of the present invention are closely combined with modern information technology to accurately capture the thulium-doped fiber spectrum data, pulsed fiber temperature data, laser output parameters and target tissue ablation data, and then obtain the thulium-doped ion concentration uniformity index, laser energy intensity and ablation index of each small target tissue ablation area, achieving real-time analysis of the uniformity of thulium-doped ion concentration distribution and the degree of target tissue ablation. Comprehensive monitoring, by constructing a thermal map matrix and anti-counterfeiting color coding maps to locate abnormal areas, solves the problems of low gain efficiency and inaccurate monitoring of the ablation degree of target tissue caused by uneven thulium ion concentration in traditional medical mid-infrared pulsed fiber lasers, ensuring that the method of the present invention can refine the dynamic monitoring standards for a medical mid-infrared 1720nm pulsed fiber laser within a more precise range, making the monitoring data a more accurate indicator under the same conditions. The development and application of this method have significantly enhanced the level of intelligence in the use of medical mid-infrared 1720n pulsed fiber lasers. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0056] Figure 1 This is a flow chart of a medical mid-infrared 1720nm pulsed fiber laser of the present invention. DETAILED DESCRIPTION

[0057] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0058] like Figure 1 As shown, the present invention provides a medical mid-infrared 1720nm pulsed fiber laser, which is composed of the following steps:

[0059] Step 101: Collect pulsed fiber laser data. The pulsed fiber laser data includes thulium-doped fiber spectrum data, pulsed fiber data, laser data, and target tissue data, providing a data basis for the implementation of subsequent steps.

[0060] Step 102: Extract features from the thulium-doped fiber spectrum data and combine it with the pulse fiber data to obtain thulium-doped fiber ion concentration distribution assessment data, and perform normalization processing on the data to eliminate dimensionality problems in subsequent calculations. Then, calculate the thulium-doped ion concentration uniformity index and evaluate the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped fiber segment.

[0061] Step 103: Using the laser data, calculate the laser output wavelength accuracy. Combined with the pulsed fiber temperature data and a multivariate linear regression algorithm, construct a laser energy intensity output model to obtain the corresponding laser energy intensity. Using the target tissue data, calculate the ablation index of each small target tissue ablation area, analyze the ablation degree of each small target tissue ablation area, and number the ablation degree of each small target tissue ablation area.

[0062] Step 104: constructing a heat map matrix of each small thulium-doped fiber segment based on the uniformity of the thulium ion concentration distribution in each small thulium-doped fiber segment; and drawing an anti-counterfeiting color-coded map of each small target tissue ablation region based on the degree of ablation in each small target tissue ablation region;

[0063] Step 105 , combining the laser energy intensity, the ablation degree number of each small target tissue ablation area, and the convolutional neural network algorithm to construct a target tissue damage analysis model;

[0064] Step 106, based on the thermal map matrix of each small thulium-doped fiber segment and the anti-counterfeiting color coding map of each target tissue ablation area, respectively analyze the uniformity of the distribution of thulium-doped ion concentration in each small thulium-doped fiber segment and the ablation degree of each small target tissue ablation area, and based on the number of each small thulium-doped fiber segment and the number of each small target tissue ablation area, respectively locate each small thulium-doped fiber segment corresponding to the abnormal uniformity of the thulium-doped ion concentration distribution and each target tissue ablation area corresponding to the abnormal ablation degree, and take corresponding measures to improve the problems of abnormal uniformity of the thulium-doped ion concentration distribution and abnormal ablation degree.

[0065] In step 101, the process of collecting pulsed fiber laser data includes:

[0066] Divide the thulium-doped optical fiber into several segments to obtain each small thulium-doped optical fiber segment, and divide the target tissue ablation area into several areas of equal area to obtain each small target tissue ablation area;

[0067] Deploy different types of acquisition equipment to collect thulium-doped fiber spectral data, pulsed fiber data, laser data, and target tissue data. These different types of acquisition equipment include broadband light sources, optical spectrum analyzers, laser pump sources, tunable lasers, optical power meters, distributed fiber temperature measurement systems, optical time-domain reflectometers, wavelength meters, spot analyzers, high-speed photodetectors, oscilloscopes, photoacoustic imaging systems, backscattered light diagnostic systems, optical coherence tomography systems, and fiber Bragg grating temperature monitoring systems.

[0068] Thulium-doped fiber spectral data includes the absorption spectrum, fluorescence spectrum, and gain spectrum of trivalent thulium ions in the thulium-doped fiber; pulse fiber data includes the temperature and length of each section of the pulse fiber; laser data includes the actual output laser wavelength of the laser, the spot diameter when the laser beam acts on the tissue surface, and the pulse frequency of the laser pulse sequence; target tissue data includes the photoacoustic signal intensity, backscattered light intensity, thermal damage depth, and temperature of the ablation area of ​​the target tissue when the laser is applied;

[0069] The above-mentioned pulse optical fiber includes thulium-doped optical fiber and other types of optical fibers. The main type of pulse optical fiber used in the realization of the function of a medical mid-infrared 1720nm pulsed fiber laser in the present invention is thulium-doped optical fiber. Therefore, the uniformity of the thulium-doped optical fiber ion concentration distribution can be evaluated by analyzing the evaluation data of the thulium-doped optical fiber ion concentration distribution.

[0070] Specifically, a broadband light source and a spectrum analyzer are combined to collect the absorption spectrum of trivalent thulium ions in thulium-doped optical fiber; a spectrum analyzer and a laser pump source are combined to collect the fluorescence spectrum of trivalent thulium ions in thulium-doped optical fiber; a tunable laser, an optical power meter and a spectrum analyzer are combined to collect the gain spectrum of trivalent thulium ions in thulium-doped optical fiber; a distributed optical fiber temperature measurement system and an optical time domain reflectometer are used to collect the temperature and length of each section of the pulse optical fiber; a wavelength meter and a spot analyzer are used to collect the actual output laser wavelength of the laser and the spot diameter when the laser beam acts on the tissue surface; a high-speed photodetector and an oscilloscope are used to collect the pulse frequency of the laser pulse sequence; a photoacoustic imaging system, a backscattered light diagnostic system, an optical coherence tomography system and a fiber Bragg grating temperature monitoring system are used to collect the photoacoustic signal intensity, backscattered light intensity, thermal damage depth and temperature of the ablation area of ​​the target tissue when the target tissue is acted on by the laser;

[0071] The pulse fiber data, laser data and target tissue data are cleaned and normalized, and the thulium-doped fiber spectrum data are subjected to baseline correction, wavelength calibration and spectrum smoothing. The baseline correction is used to eliminate the interference of the fiber matrix material, detector noise or ambient light; the wavelength calibration is used to correct the wavelength accuracy error of the spectrometer; the spectrum smoothing is used to reduce high-frequency noise and highlight the characteristic peaks. Timestamps are assigned to each type of preprocessed pulse fiber laser data, and the assigned timestamps are adjusted to achieve synchronization of the acquisition time of the thulium-doped fiber spectrum data, pulse fiber data, laser data and target tissue data. The thulium-doped fiber spectrum data, pulse fiber data, laser data and target tissue data are integrated to generate a pulse fiber laser data set.

[0072] In step 102, the process of obtaining the thulium-doped optical fiber ion concentration distribution evaluation data through feature extraction and performing normalization processing on the data includes:

[0073] The evaluation data of thulium-doped fiber ion concentration distribution include the absorption coefficient, gain coefficient and gain saturation threshold power of each small thulium-doped fiber segment, as well as the peak wavelength and full width at half maximum of the fluorescence spectrum corresponding to each small thulium-doped fiber segment;

[0074] A characteristic peak detection algorithm is used to identify the characteristic absorption peak wavelength of trivalent thulium ions from the absorption spectrum of trivalent thulium ions in thulium-doped optical fiber. According to the rare earth ion spectrum theory, the energy level transition corresponding to the characteristic absorption peak of trivalent thulium ions is determined. The absorbance is read at the characteristic absorption peak wavelength of trivalent thulium ions. According to the Lambert-Beer law and the length of each pulse optical fiber segment, the absorption coefficient of each small thulium-doped optical fiber segment is calculated. The calculation formula is: Among them, α x is the absorption coefficient of each small thulium-doped fiber segment, A xis the absorbance read at the characteristic absorption peak wavelength of trivalent thulium ion, and L is the length of each pulse fiber segment;

[0075] Using spectral analysis technology, the fluorescence intensity and wavelength are extracted from the fluorescence spectrum of trivalent thulium ions in thulium-doped optical fiber. Combined with the derivative method, the peak position of the fluorescence spectrum is determined, and then the corresponding peak wavelength is determined. Based on the peak wavelength of the fluorescence spectrum, the two fluorescence wavelengths corresponding to half the fluorescence intensity are extracted. The absolute value of the difference between the two extracted fluorescence wavelengths is used to calculate the half-maximum full width of the fluorescence spectrum corresponding to each small thulium-doped optical fiber segment.

[0076] Combining the signal gain linear fitting method and the saturation curve nonlinear fitting method, the gain coefficient and gain saturation threshold power of each small thulium-doped fiber segment are extracted from the gain spectrum of trivalent thulium ions in the thulium-doped fiber.

[0077] The absorption coefficient, gain coefficient and gain saturation threshold power of each small thulium-doped fiber segment extracted from the features, as well as the peak wavelength and half-maximum full width of the fluorescence spectrum of each small thulium-doped fiber segment are subjected to Z-score normalization. The Z-score normalization formula is: Among them, x ' is the data after Z-score normalization, x is the actual value of the data, is the data mean, σ is the data standard deviation, and the specific calculation process is: first, calculate the mean and standard deviation of each thulium-doped fiber ion concentration distribution evaluation data extracted by features, and substitute each thulium-doped fiber ion concentration distribution evaluation data and its mean and standard deviation into the Z-score normalization formula to realize the Z-score normalization processing of the thulium-doped fiber ion concentration distribution evaluation data.

[0078] In step 102, the process of calculating the thulium-doped ion concentration uniformity index and evaluating the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped optical fiber segment includes:

[0079] The weighted average dispersion method is used to combine the thulium-doped fiber ion concentration distribution evaluation data after Z-score normalization to calculate the thulium-doped ion concentration uniformity index. The specific calculation process includes: first, calculating the standard deviation and mean of each thulium-doped fiber ion concentration distribution evaluation data after Z-score normalization respectively, and using the ratio of the standard deviation to the mean of each thulium-doped fiber ion concentration distribution evaluation data to obtain the absorption coefficient dispersion coefficient, gain coefficient dispersion coefficient, gain saturation threshold power dispersion coefficient, and peak wavelength dispersion coefficient and half-maximum full width dispersion coefficient of the fluorescence spectrum respectively, and assigning weights to the absorption coefficient dispersion coefficient, gain coefficient dispersion coefficient, gain saturation threshold power dispersion coefficient, and peak wavelength dispersion coefficient and half-maximum full width dispersion coefficient of the fluorescence spectrum respectively. The formula for calculating the thulium-doped ion concentration uniformity index is: U=1-(wα α+w g g+w p p sat +w γ γ spec +w β β d ), where U is the uniformity index of thulium ion concentration, w α , w g , w p , w γ and w β are the weights of the absorption coefficient dispersion coefficient, gain coefficient dispersion coefficient, gain saturation threshold power dispersion coefficient, and peak wavelength dispersion coefficient and half-maximum full width dispersion coefficient of the fluorescence spectrum, α, g, p sat , γ spec and β d They are the dispersion coefficient of absorption coefficient, dispersion coefficient of gain coefficient, dispersion coefficient of gain saturation threshold power, and dispersion coefficient of peak wavelength and full width at half maximum of fluorescence spectrum;

[0080] When the thulium-doped ion concentration uniformity index is lower than 0.25, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a low distribution uniformity; when the thulium-doped ion concentration uniformity index is between 0.25 and 0.45, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a medium distribution uniformity; when the thulium-doped ion concentration uniformity index is higher than 0.45, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a high distribution uniformity.

[0081] In step 103, the laser output wavelength accuracy is calculated, and a laser energy intensity output model is constructed by combining a multivariate linear regression algorithm to obtain the corresponding laser energy intensity. The process includes:

[0082] The target output laser wavelength of the laser was set to 1720 nm. The laser output wavelength accuracy was calculated using the absolute value of the difference between the actual laser output wavelength and the target output laser wavelength. The laser output wavelength accuracy was normalized using the Z-score and then integrated into the pulsed fiber laser dataset.

[0083] The temperature of each pulse fiber segment, the spot diameter of the laser beam when it impacts the tissue surface, the pulse frequency of the laser pulse sequence, and the accuracy of the laser output wavelength were extracted from the pulse fiber laser data set. The extracted data were divided into a first training set and a first test set in an 8:2 ratio.

[0084] Using the first training set data and combining it with a multivariate linear regression algorithm, the first training set data is used as input and the laser energy intensity is used as output. The linear relationship between the temperature of each segment of the pulsed optical fiber, the spot diameter when the laser beam acts on the tissue surface, the pulse frequency of the laser pulse sequence, the laser output wavelength accuracy and the laser energy intensity is learned to train a laser energy intensity output model.

[0085] The first test set data is input into the laser energy intensity output model, and the regression coefficient and intercept term of the laser energy intensity output model are adjusted to optimize the performance of the laser energy intensity output model. The laser energy intensity output model is obtained. The expression of the laser energy intensity output model is as follows:

[0086]

[0087] Where E is the laser energy intensity, and are the regression coefficients of the laser energy intensity output model, T, R, F and D are the temperature of each pulse fiber segment, the spot diameter when the laser beam acts on the tissue surface, the pulse frequency of the laser pulse sequence and the laser output wavelength accuracy, respectively. and θ are the intercept term and error term of the laser energy intensity output model, respectively;

[0088] Combined with the current temperature of each section of pulsed optical fiber, the spot diameter when the laser beam acts on the tissue surface, the pulse frequency of the laser pulse sequence and the accuracy of the laser output wavelength, the corresponding laser energy intensity is output and integrated into the pulsed fiber laser data set.

[0089] In step 103, the process of calculating the ablation index of each small target tissue ablation area, analyzing the ablation degree of each small target tissue ablation area, and numbering the ablation degree of each small target tissue ablation area includes:

[0090] The principle of collaboratively evaluating the ablation degree of each small target tissue ablation area based on the target tissue data can be understood as follows: the intensity of the photoacoustic signal when the ablation area of ​​the target tissue is exposed to laser action reflects the energy absorption efficiency and is the prerequisite for ablation; the intensity of the backscattered light when the ablation area of ​​the target tissue is exposed to laser action reflects the degree of tissue structure damage; the depth of the thermal damage when the ablation area of ​​the target tissue is exposed to laser action reflects the ablation range; the temperature of the ablation area of ​​the target tissue when exposed to laser action reflects the intensity of the thermal effect. The ablation index of each small target tissue ablation area is calculated using the preprocessed target tissue data in combination with the nonlinear product model formula. The calculation process is as follows:

[0091]

[0092] Among them, AQi The ablation index of each small target tissue ablation area, and are the normalized photoacoustic signal intensity, backscattered light intensity, thermal damage depth, and temperature of the ablation area of ​​the target tissue when it is acted upon by the laser, and i is the number of ablation areas of each small target tissue;

[0093] When the ablation index of each small target tissue ablation area is lower than 0.35, it corresponds to a low degree of ablation; when the ablation index of each small target tissue ablation area is between 0.35 and 0.7, it corresponds to a medium degree of ablation; when the ablation index of each small target tissue ablation area is higher than 0.7, it corresponds to a high degree of ablation;

[0094] Numbering the ablation degree of each small target tissue ablation area, and integrating the ablation degree and number of each small target tissue ablation area into the pulsed fiber laser data set;

[0095] In step 104, the process of constructing the thermal map matrix of each small thulium-doped fiber segment includes:

[0096] Number each small thulium-doped fiber segment, determine the heat map matrix structure, set the row dimension to the number of each small thulium-doped fiber segment, arrange them in ascending order of the number of each small thulium-doped fiber segment, and set the column dimension to the distribution uniformity of the thulium ion concentration in each small thulium-doped fiber segment;

[0097] According to the color mapping rules, continuous color scales are used to represent the high distribution uniformity, medium distribution uniformity and low distribution uniformity of the thulium ion concentration in each small thulium-doped fiber segment from light to dark, and a heat map matrix of each small thulium-doped fiber segment is constructed;

[0098] The explanation of the heat map matrix is: the heat map matrix of each small thulium-doped fiber segment is used to display the distribution uniformity of the thulium-doped fiber concentration in each small thulium-doped fiber segment and its corresponding number. The corresponding small thulium-doped fiber segment can be retrieved according to the number. When subsequent measures are taken, only the small thulium-doped fiber segment corresponding to the number is required, which reduces cost and resources and also realizes the positioning of each small thulium-doped fiber segment corresponding to the abnormal distribution uniformity of the thulium-doped fiber concentration.

[0099] In step 104, the process of drawing the anti-counterfeiting color-coded map of each target tissue ablation area includes:

[0100] Using color coding technology, green, yellow, and red were selected, and the printed colors were calibrated using Pantone color charts to ensure color accuracy. Green, yellow, and red were associated with low, medium, and high ablation levels in each small target tissue ablation area, respectively.

[0101] Combined with the numbering and labeling technology, each small target tissue ablation area is labeled according to its number, and each small target tissue ablation area is arranged in the order of number using vector graphics software;

[0102] The printing accuracy needs to be adjusted to above 300dpi to ensure that the micron-level texture is clearly discernible, as distortion is prone to occur during copying, and then an anti-counterfeiting color-coded map of each target tissue ablation area is drawn.

[0103] In step 105, the process of constructing the target tissue damage analytical model includes:

[0104] Extracting the laser energy intensity and the ablation degree number of each small target tissue ablation area from the pulsed fiber laser data set, and dividing the currently extracted data into a second training set and a second test set, with the ratio of the second training set to the second test set being 7:3;

[0105] Combining the second training set data with a convolutional neural network algorithm, the laser energy intensity is used as input and the ablation degree number of each small target tissue ablation area is used as output. The nonlinear relationship between the laser energy intensity and the ablation degree number of each small target tissue ablation area is learned to train the target tissue damage analysis model.

[0106] Inputting the second test set data into the target tissue damage analytical model, comparing the output of the target tissue damage analytical model with the ablation degree number of each actual small target tissue ablation area, evaluating the performance of the target tissue damage analytical model, adjusting the parameters of the target tissue damage analytical model, optimizing the target tissue damage analytical model, and thus obtaining the final target tissue damage analytical model;

[0107] Through the target tissue damage analysis model, the nonlinear relationship between the laser energy intensity and the ablation degree number of each small target tissue ablation area is obtained. By continuously adjusting the target tissue damage analysis model parameters, the accuracy of the target tissue damage analysis model output results is improved. In the subsequent monitoring of the ablation degree of each small target tissue ablation area, the precise ablation degree of each small target tissue ablation area can be obtained by analyzing the laser energy intensity, and then the anti-counterfeiting color coding map of each target tissue ablation area is updated, saving the monitoring cost.

[0108] In step 106, the process of evaluating each target tissue ablation area corresponding to abnormal thulium-doped ion concentration uniformity and abnormal ablation degree and taking corresponding measures to improve the area includes:

[0109] Analyze the thermal map matrix of each small thulium-doped fiber segment, and obtain the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped fiber segment according to the color depth of the continuous color scale. Retrieve the corresponding small thulium-doped fiber segment number based on the row dimension. When the thulium-doped ion concentration in the small thulium-doped fiber segment is highly uniform, it indicates that the thulium-doped ions are uniformly distributed in the fiber core layer without concentration gradient, the pump light absorption efficiency is high and uniform, and the laser mode is stable. The existing fiber manufacturing process of the corresponding small thulium-doped fiber segment is retained to ensure the stability of the doping uniformity. A pump source matching the fiber absorption peak is used to maximize the energy coupling efficiency. It can be used for high-precision surgery and the stable laser output brought by high uniformity can achieve the advantages of clear tissue ablation boundaries and small thermal damage. When the thulium-doped ion concentration in the small thulium-doped fiber segment is moderately uniform, it indicates that there are slight local concentration fluctuations of the thulium-doped ions, which may cause local overheating or mode instability. The inner cladding gradient refractive index design is adopted to compensate for the pump light absorption unevenness caused by the ion concentration gradient by adjusting the inner cladding diameter or doping distribution, optimize the heat conduction efficiency of the clamping structure of the corresponding small thulium-doped fiber segment, and promptly remove the heat generated by local hot spots to avoid the glass matrix from cracking due to thermal stress. The pulse width modulation technology is used to shorten the high-power pulse duration in the corresponding small thulium-doped fiber segment and reduce the heat accumulation effect. When the thulium-doped ion concentration in the small thulium-doped fiber segment is of low distribution uniformity, it indicates that the thulium-doped ion concentration presents significant spatial inhomogeneity, which may cause serious mode distortion, power hopping or fiber damage. Unqualified small thulium-doped fiber segments are eliminated, and the segmented pumping technology is adopted to set an independent pump source in the corresponding small thulium-doped fiber segment. The pump energy of each segment is dynamically adjusted according to the concentration distribution. The chirped pulse amplification technology is introduced to broaden, amplify and compress the pulse sequence, reduce the peak power density, and avoid nonlinear effects such as self-phase modulation and four-wave mixing.

[0110] According to the color of each small target tissue ablation area in the anti-counterfeiting color coding map of each target tissue ablation area, analyze the ablation degree of each small target tissue ablation area, and retrieve the number corresponding to each small target tissue ablation area according to the number label. When the small target tissue ablation area is green, it corresponds to a low ablation degree, indicating that the corresponding small target tissue ablation area has only slight thermal damage and has not reached the coagulation or vaporization threshold. The ablation plan of the corresponding small target tissue ablation area is maintained; when the small target tissue ablation area is yellow, it corresponds to a medium ablation degree, indicating that the corresponding small target tissue ablation area has coagulative necrosis and there is a reversible thermal damage zone at the edge. , intermittent irradiation is used, and thermal relaxation time is used to reduce the damage to the ablation area of ​​small target tissue with normal peripheral ablation degree. Single-point irradiation is changed to spiral scanning and fence scanning to evenly cover the corresponding small target tissue ablation area and reduce local excessive ablation; when the ablation area of ​​small target tissue is red, it corresponds to a high degree of ablation, indicating that the tissue is vaporized, carbonized or even perforated, and there is irreversible thermal damage at the edge, which may be accompanied by the risk of bleeding and perforation. Use saline spray and low-temperature gas to cool the corresponding small target tissue ablation area to below 37°C, reduce the expansion of the carbonization range, and combine laser with other energy forms to complement the ablation needs.

[0111] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A medical mid-infrared 1720nm pulsed fiber laser, characterized by: The following steps are involved: Collecting pulsed fiber laser data, the pulsed fiber laser data including thulium-doped fiber spectrum data, pulsed fiber data, laser data, and target tissue data; Extracting features from the thulium-doped fiber spectrum data, combining it with pulse fiber data, obtaining thulium-doped fiber ion concentration distribution assessment data, and normalizing it to calculate the thulium-doped ion concentration uniformity index, and evaluating the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped fiber segment; Using the laser data, the laser output wavelength accuracy is calculated. Combining the pulsed fiber temperature data with a multivariate linear regression algorithm, a laser energy intensity output model is constructed to obtain the corresponding laser energy intensity. Using the target tissue data, the ablation index of each small target tissue ablation area is calculated, the ablation degree of each small target tissue ablation area is analyzed, and the ablation degree of each small target tissue ablation area is numbered. Constructing a heat map matrix of each small thulium-doped fiber segment based on the uniformity of the distribution of thulium ion concentration in each small thulium-doped fiber segment; and drawing an anti-counterfeiting color-coded map of each small target tissue ablation area based on the degree of ablation of each small target tissue ablation area; Combining the laser energy intensity, the ablation degree number of each small target tissue ablation area, and a convolutional neural network algorithm, a target tissue damage analysis model is constructed; According to the thermal map matrix of each small thulium-doped optical fiber segment and the anti-counterfeiting color coding map of each target tissue ablation area, the distribution uniformity of the thulium ion concentration in each small thulium-doped optical fiber segment and the ablation degree of each small target tissue ablation area are analyzed respectively. According to the number of each small thulium-doped optical fiber segment and the number of each small target tissue ablation area, the small thulium-doped optical fiber segment corresponding to the abnormal uniformity of the thulium ion concentration distribution and the target tissue ablation area corresponding to the abnormal ablation degree are located respectively, and corresponding measures are taken to improve the problems of abnormal uniformity of the thulium ion concentration distribution and abnormal ablation degree.

2. A medical mid-infrared 1720 nm pulsed fiber laser according to claim 1, characterized in that: The pulse fiber laser data acquisition process includes: Divide the thulium-doped optical fiber into several segments to obtain each small thulium-doped optical fiber segment, and divide the target tissue ablation area into several areas of equal area to obtain each small target tissue ablation area; Deploy different types of acquisition equipment to collect thulium-doped fiber spectral data, pulsed fiber data, laser data, and target tissue data, wherein the different types of acquisition equipment include broadband light sources, optical spectrum analyzers, laser pump sources, tunable lasers, optical power meters, distributed fiber temperature measurement systems, optical time domain reflectometers, wavelength meters, spot analyzers, high-speed photodetectors, oscilloscopes, photoacoustic imaging systems, backscattered light diagnostic systems, optical coherence tomography systems, and fiber Bragg grating temperature monitoring systems; The thulium-doped fiber spectral data includes the absorption spectrum, fluorescence spectrum and gain spectrum of trivalent thulium ions in the thulium-doped fiber; the pulse fiber data includes the temperature and length of each section of the pulse fiber; the laser data includes the actual output laser wavelength of the laser, the spot diameter when the laser beam acts on the tissue surface and the pulse frequency of the laser pulse sequence; the target tissue data includes the photoacoustic signal intensity, backscattered light intensity, thermal damage depth and temperature of the ablation area of ​​the target tissue when it is acted upon by the laser; The pulse fiber data, the laser data, and the target tissue data are cleaned and normalized, and the thulium-doped fiber spectrum data are baseline corrected, wavelength calibrated, and spectral smoothed. Timestamps are assigned to each type of preprocessed pulse fiber laser data, and the assigned timestamps are adjusted to achieve acquisition time synchronization of the thulium-doped fiber spectrum data, the pulse fiber data, the laser data, and the target tissue data. The thulium-doped fiber spectrum data, the pulse fiber data, the laser data, and the target tissue data are integrated to generate a pulse fiber laser data set.

3. A medical mid-infrared 1720 nm pulsed fiber laser according to claim 2, characterized in that: The process of obtaining thulium-doped optical fiber ion concentration distribution evaluation data through feature extraction and normalizing the data includes: The thulium-doped fiber ion concentration distribution evaluation data includes the absorption coefficient, gain coefficient and gain saturation threshold power of each small thulium-doped fiber segment, and the peak wavelength and half-maximum full width of the fluorescence spectrum corresponding to each small thulium-doped fiber segment; A characteristic peak detection algorithm is used to identify the characteristic absorption peak wavelength of the trivalent thulium ion from the absorption spectrum of the trivalent thulium ion in the thulium-doped optical fiber. Based on the rare earth ion spectrum theory, the energy level transition corresponding to the characteristic absorption peak of the trivalent thulium ion is determined. The absorbance is read at the characteristic absorption peak wavelength of the trivalent thulium ion. The absorption coefficient of each small thulium-doped optical fiber segment is calculated based on the Lambert-Beer law and the length of each pulse optical fiber segment. Using spectral analysis technology, the fluorescence intensity and wavelength are extracted from the fluorescence spectrum of trivalent thulium ions in the thulium-doped optical fiber. Combined with the derivative method, the peak position of the fluorescence spectrum is determined, and then the corresponding peak wavelength is determined. Based on the peak wavelength of the fluorescence spectrum, two fluorescence wavelengths corresponding to half the fluorescence intensity are extracted. The full width at half maximum of the fluorescence spectrum corresponding to each small thulium-doped optical fiber segment is calculated by the absolute value of the difference between the two extracted fluorescence wavelengths. Combining the signal gain linear fitting method and the saturation curve nonlinear fitting method, the gain coefficient and the gain saturation threshold power of each small thulium-doped fiber segment are extracted from the gain spectrum of the trivalent thulium ion in the thulium-doped fiber; The absorption coefficient, gain coefficient and gain saturation threshold power of each small thulium-doped fiber segment extracted from the features, as well as the peak wavelength and half-maximum full width of the fluorescence spectrum corresponding to each small thulium-doped fiber segment are subjected to Z-score normalization processing.

4. A medical mid-infrared 1720 nm pulsed fiber laser according to claim 3, characterized in that: The process of calculating the thulium-doped ion concentration uniformity index and evaluating the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped optical fiber segment includes: The thulium-doped ion concentration uniformity index is calculated by using the weighted average dispersion method and the Z-score normalized thulium-doped optical fiber ion concentration distribution evaluation data; When the thulium-doped ion concentration uniformity index is lower than 0.25, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a low distribution uniformity; when the thulium-doped ion concentration uniformity index is between 0.25 and 0.45, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a medium distribution uniformity; when the thulium-doped ion concentration uniformity index is higher than 0.45, the thulium-doped ion concentration in each small thulium-doped fiber segment corresponds to a high distribution uniformity.

5. The medical mid-infrared 1720 nm pulsed fiber laser according to claim 4, characterized in that: The process of calculating the laser output wavelength accuracy, combining the multiple linear regression algorithm, building a laser energy intensity output model, and then obtaining the corresponding laser energy intensity includes: The target output laser wavelength of the laser is set to 1720 nm. The laser output wavelength accuracy is calculated by the absolute value of the difference between the actual output laser wavelength and the target output laser wavelength. The laser output wavelength accuracy is normalized by Z-score and then integrated into the pulsed fiber laser dataset. Extracting the temperature of each segment of the pulsed fiber, the spot diameter of the laser beam when it acts on the tissue surface, the pulse frequency of the laser pulse sequence, and the accuracy of the laser output wavelength from the pulsed fiber laser data set, and dividing the extracted data into a first training set and a first test set; Using the first training set data in combination with a multivariate linear regression algorithm, with the first training set data as input and the laser energy intensity as output, the linear relationship between the temperature of each segment of the pulsed optical fiber, the spot diameter of the laser beam when it acts on the tissue surface, the pulse frequency of the laser pulse sequence, the laser output wavelength accuracy, and the laser energy intensity is learned to train a laser energy intensity output model; Inputting the first test set data into the laser energy intensity output model, adjusting the regression coefficient and intercept term of the laser energy intensity output model, optimizing the performance of the laser energy intensity output model, and obtaining the laser energy intensity output model; Combined with the current temperature of each section of the pulsed optical fiber, the spot diameter of the laser beam when it acts on the tissue surface, the pulse frequency of the laser pulse sequence and the accuracy of the laser output wavelength, the corresponding laser energy intensity is output and integrated into the pulsed fiber laser data set.

6. The medical mid-infrared 1720 nm pulsed fiber laser according to claim 5, characterized in that: The process of calculating the ablation index of each small target tissue ablation area, analyzing the ablation degree of each small target tissue ablation area, and numbering the ablation degree of each small target tissue ablation area includes: Based on the principle of collaboratively evaluating the ablation degree of each small target tissue ablation area using the target tissue data, the ablation index of each small target tissue ablation area is calculated using the preprocessed target tissue data in combination with the nonlinear product model formula. The calculation process is as follows: Among them, AQ i The ablation index of each small target tissue ablation area, and are the normalized photoacoustic signal intensity, backscattered light intensity, thermal damage depth, and temperature of the ablation area of ​​the target tissue when it is acted upon by the laser, and i is the number of ablation areas of each small target tissue; When the ablation index of each small target tissue ablation area is lower than 0.35, it corresponds to a low degree of ablation; when the ablation index of each small target tissue ablation area is between 0.35 and 0.7, it corresponds to a medium degree of ablation; when the ablation index of each small target tissue ablation area is higher than 0.7, it corresponds to a high degree of ablation; The ablation degree of each small target tissue ablation area is numbered, and the ablation degree and number of each small target tissue ablation area are integrated into the pulse fiber laser data set.

7. The medical mid-infrared 1720 nm pulsed fiber laser according to claim 6, characterized in that: The process of constructing the thermal map matrix of each small thulium-doped optical fiber segment includes: Number each small thulium-doped fiber segment, determine the heat map matrix structure, set the row dimension to the number of each small thulium-doped fiber segment, arrange them in ascending order of the number of each small thulium-doped fiber segment, and set the column dimension to the distribution uniformity of the thulium ion concentration in each small thulium-doped fiber segment; According to the color mapping rules, continuous color scales are used to represent the high distribution uniformity, medium distribution uniformity and low distribution uniformity of the thulium ion concentration in each small thulium-doped fiber segment from light to dark, and a heat map matrix of each small thulium-doped fiber segment is constructed.

8. The medical mid-infrared 1720 nm pulsed fiber laser according to claim 7, characterized in that: The process of drawing the anti-counterfeiting color coding map of each target tissue ablation area includes: Using color coding technology, green, yellow, and red are selected, and printed colors are calibrated using a Pantone color chart, and green, yellow, and red are associated with low, medium, and high ablation degrees of each small target tissue ablation area, respectively; In combination with the numbering and labeling technology, each small target tissue ablation area is labeled according to the number of each small target tissue ablation area, and each small target tissue ablation area is arranged in the order of the number using vector graphics software; The printing accuracy needs to be adjusted to above 300 dpi, and then an anti-counterfeiting color-coded map of each target tissue ablation area is drawn.

9. The medical mid-infrared 1720 nm pulsed fiber laser according to claim 8, characterized in that: The process of constructing the target tissue damage analytical model includes: Extracting the laser energy intensity and the ablation degree number of each small target tissue ablation area from the pulsed fiber laser data set, and dividing the currently extracted data into a second training set and a second test set; Combining the second training set data with a convolutional neural network algorithm, using laser energy intensity as input and the ablation degree number of each small target tissue ablation area as output, learning the nonlinear relationship between laser energy intensity and the ablation degree number of each small target tissue ablation area, and training the target tissue damage analysis model; The second test set data is input into the target tissue damage analysis model, and the output results of the target tissue damage analysis model are compared with the actual ablation degree numbers of each small target tissue ablation area to evaluate the performance of the target tissue damage analysis model, adjust the parameters of the target tissue damage analysis model, optimize the target tissue damage analysis model, and then obtain the final target tissue damage analysis model.

10. The medical mid-infrared 1720 nm pulsed fiber laser according to claim 9, characterized in that: The process of evaluating each target tissue ablation area corresponding to abnormal thulium-doped ion concentration uniformity and abnormal ablation degree and taking corresponding measures to improve the area includes: Analyze the thermal map matrix of each small thulium-doped fiber segment, obtain the distribution uniformity of the thulium-doped ion concentration in each small thulium-doped fiber segment according to the color depth of the continuous color scale, and retrieve the corresponding small thulium-doped fiber segment number based on the row dimension. When the thulium-doped ion concentration in the small thulium-doped fiber segment is highly uniformly distributed, retain the existing fiber manufacturing process of the corresponding small thulium-doped fiber segment, and use a pump source that matches the fiber absorption peak to maximize the energy coupling efficiency; when the thulium-doped ion concentration in the small thulium-doped fiber segment is moderately uniformly distributed, The inner cladding gradient refractive index design is adopted to optimize the heat conduction efficiency of the clamping structure of the corresponding small thulium-doped fiber segment, and the pulse width modulation technology is used to shorten the high-power pulse duration of the corresponding small thulium-doped fiber segment; when the thulium ion concentration in the small thulium-doped fiber segment is of low distribution uniformity, the unqualified small thulium-doped fiber segment is eliminated, and the segmented pumping technology is adopted to set an independent pump source in the corresponding small thulium-doped fiber segment. The pump energy of each segment is dynamically adjusted according to the concentration distribution, and the chirped pulse amplification technology is introduced to broaden, amplify and compress the pulse sequence to reduce the peak power density; According to the color of each small target tissue ablation area in the anti-counterfeiting color-coded map of each target tissue ablation area, the ablation degree of each small target tissue ablation area is analyzed, and the number corresponding to each small target tissue ablation area is retrieved according to the number label. When the small target tissue ablation area is green, it corresponds to a low ablation degree, and the ablation plan of the corresponding small target tissue ablation area is maintained; when the small target tissue ablation area is yellow, it corresponds to a medium ablation degree, and intermittent irradiation is used to use the thermal relaxation time to reduce the damage to the small target tissue ablation area with normal peripheral ablation degree. The single-point irradiation is changed to spiral scanning and fence scanning to evenly cover the corresponding small target tissue ablation area and reduce local excessive ablation; when the small target tissue ablation area is red, it corresponds to a high ablation degree, and physiological saline spray and low-temperature gas are used to cool the corresponding small target tissue ablation area to below 37°C to reduce the expansion of the carbonization range. Laser and other energy forms are combined to complement and adjust the ablation needs.

Images