WO2026001663A1 - Procédé de construction de modèle de détermination de puissance de laser et procédé de réglage automatique de puissance de laser - Google Patents

Procédé de construction de modèle de détermination de puissance de laser et procédé de réglage automatique de puissance de laser

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Publication number
WO2026001663A1
WO2026001663A1 PCT/CN2025/100098 CN2025100098W WO2026001663A1 WO 2026001663 A1 WO2026001663 A1 WO 2026001663A1 CN 2025100098 W CN2025100098 W CN 2025100098W WO 2026001663 A1 WO2026001663 A1 WO 2026001663A1
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WIPO (PCT)
Prior art keywords
laser power
fiber core
solution
brightness
average
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PCT/CN2025/100098
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English (en)
Chinese (zh)
Inventor
段西尧
冯宇
马骁萧
丁莽
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Viestar Hubei Medical Technology Co Ltd
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Viestar Hubei Medical Technology Co Ltd
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Publication date
Priority claimed from CN202410852246.5A external-priority patent/CN118736350A/zh
Priority claimed from CN202410852114.2A external-priority patent/CN118717002A/zh
Application filed by Viestar Hubei Medical Technology Co Ltd filed Critical Viestar Hubei Medical Technology Co Ltd
Publication of WO2026001663A1 publication Critical patent/WO2026001663A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting

Definitions

  • This application relates to the field of endoscopic imaging, and more specifically, to a method for constructing a laser power determination model and a method for automatically adjusting laser power.
  • Confocal endoscopy is a medical device that can be inserted into the human body through channels such as gastroscopes and colonoscopes to obtain local histological images, enabling precise diagnosis of tiny lesions, gastrointestinal diseases, and early gastrointestinal cancers.
  • the basic principle of confocal endoscopy is to illuminate tissue with a laser and then detect the fluorescence reflected from the tissue. Under the condition of a certain concentration of fluorescent dye, different laser powers will produce images of varying quality. Excessively high or low laser power will result in images that are too bright or too dark, making it impossible to distinguish details and lacking sufficient contrast, thus reducing image quality. Therefore, appropriate laser power is crucial for image quality.
  • this application proposes a method for constructing a laser power determination model, the method comprising:
  • N frames of image data of the aforementioned endoscope probe in the air are acquired to construct an air environment image dataset
  • N frames of image data were acquired of the endoscope probe immersed in a sodium fluorescein solution of a reference concentration to construct a solution environment image dataset.
  • the aforementioned laser power determination model includes a first correspondence and a second correspondence.
  • the first correspondence is the correspondence between air environment image data and the aforementioned K different laser powers
  • the second correspondence is the correspondence between solution environment image data and the aforementioned K different laser powers.
  • the above-mentioned data fitting based on the above-mentioned air environment image dataset, the above-mentioned solution environment image dataset, the laser power set, and the preset curve fitting method to obtain the above-mentioned laser power determination model includes:
  • the average brightness signal values at all fiber core locations under each laser power are used to construct a set of average fiber core brightness signals in the air.
  • the average brightness signal values at all fiber core locations under each laser power are used to construct a set of average fiber core brightness signals in solution.
  • Data fitting is performed based on the above-mentioned average value set of fiber core brightness signals in air, the above-mentioned laser power set, and the above-mentioned preset curve fitting method to construct the above-mentioned first correspondence relationship;
  • the data is fitted using the average set of fiber core brightness signals in the solution, the laser power set, and the preset curve fitting method to construct the second correspondence.
  • the laser power determination model is created.
  • it further includes:
  • the fiber core is located using the aforementioned air environment image dataset or the aforementioned solution environment image dataset to obtain the fiber core position.
  • the method for obtaining the average value of the brightness signal at the aforementioned fiber core location and the average value of the fiber core brightness signal in the solution is specifically as follows:
  • the average of N frames of image data acquired at each laser power is calculated pixel by pixel to obtain the average image set in air.
  • Image set of mean values in solution
  • the average value set of fiber core brightness signal in the solution is extracted from the fiber core location located on the mean image set in the above solution.
  • the aforementioned reference concentration is the average value of the fiber core brightness signal in the reference solution.
  • the average brightness signal of the fiber core in the aforementioned reference solution is the average brightness signal of all fiber core positions extracted from the located fiber core position on the average image set in the reference solution.
  • the aforementioned average image set in the reference solution is obtained by averaging multiple frames of image data obtained by immersing the endoscope probe in the aforementioned reference concentration of fluorescein sodium solution at maximum laser power.
  • the brightness value in the preset brightness value range is the maximum brightness value that the hardware can achieve multiplied by a coefficient greater than or equal to 0.5 and less than or equal to 1.
  • this application also proposes a method for automatic adjustment of laser power in a confocal endoscope, including:
  • a model is constructed based on the current concentration, laser power, and fiber core brightness to determine the laser power corresponding to the current concentration of sodium fluorescein solution when the fiber core brightness signal just reaches the maximum brightness value achievable by the hardware.
  • the above-mentioned model for constructing the current concentration, laser power, and fiber core brightness to determine the laser power corresponding to the current concentration of sodium fluorescein solution when the fiber core brightness signal just reaches the maximum brightness value achievable by the hardware specifically includes:
  • the brightness signal value adjustment range is determined based on the maximum brightness value that the hardware can achieve, the first adjustment coefficient, and the second adjustment coefficient; the laser power adjustment range is determined based on the maximum laser power and the minimum laser power of the laser.
  • the laser power determination model is constructed based on the concentration of sodium fluorescein solution, the brightness signal value of the fiber core, and the laser power.
  • the laser power at the point where the maximum brightness value that the hardware can achieve is calculated based on the current concentration of sodium fluorescein solution.
  • the laser power at which the brightness signal reaches its maximum value is determined as the adjusted target laser power.
  • the current concentration of the sodium fluorescein solution corresponding to the current laser power is calculated based on the average of the larger brightness values, including:
  • the current concentration of sodium fluorescein solution corresponding to the current laser power is calculated.
  • the method for obtaining a valid image set includes:
  • the cached images in the cached image set are filtered to obtain the effective image set.
  • the laser power determination model construction method of this application embodiment includes: selecting K different laser powers to construct a laser power set; acquiring N frames of image data of the endoscope probe in air at each laser power to construct an air environment image dataset; acquiring N frames of image data of the endoscope probe immersed in a reference concentration of sodium fluorescein solution at each laser power to construct a solution environment image dataset; and performing data fitting based on the air environment image dataset, the solution environment image dataset, the laser power set, and a preset curve fitting method to obtain the laser power determination model.
  • the laser power determination model includes a first correspondence and a second correspondence. The first correspondence is the correspondence between the air environment image data and the K different laser powers, and the second correspondence is the correspondence between the solution environment image data and the K different laser powers.
  • the method proposed in this application embodiment by precisely controlling the laser power, automatically adjusts the laser power according to different environments (air and fluorescent dye solution), ensuring optimal image quality under various conditions.
  • This method can effectively cope with individual differences and changes in fluorescent dye concentration, ensuring moderate brightness and contrast in the image, thereby making it easier to identify details and lesions.
  • Automated laser power adjustment reduces the burden on physicians operating confocal endoscopes. Physicians do not need in-depth knowledge of how to adjust laser power based on images, reducing training requirements and minimizing human error during operation.
  • the model proposed in this application enables automated laser power adjustment, shortening equipment setup time and accelerating the diagnostic process.
  • the model in this application is adaptable to different types of confocal endoscopes and diverse clinical environments.
  • This application's embodiment establishes a laser power determination model based on actual image data, achieving automated laser power adjustment of confocal endoscopes in clinical use. This effectively improves image quality and operational efficiency while reducing the complexity of physician operations and training requirements, providing clinicians with a more efficient and accurate diagnostic tool.
  • the automatic laser power adjustment method for confocal endoscopes includes: determining a brightness signal value adjustment range based on the maximum brightness value achievable by the hardware, a first adjustment coefficient, and a second adjustment coefficient; determining a laser power adjustment range based on the maximum laser power of the laser and the maximum laser power; acquiring an effective image set using the maximum laser power as the initial laser power; acquiring a larger brightness value for each frame in the effective image set; and determining the adjusted target laser power based on the average of the larger brightness values and the brightness signal value adjustment range.
  • the method proposed in this application achieves automatic laser power adjustment, enabling the endoscope to automatically adjust to the optimal laser output during tissue imaging, thereby improving image quality, simplifying the operation process, and reducing the burden on doctors during operation.
  • Figure 1 is a flowchart illustrating a laser power determination model construction method provided in an embodiment of this application.
  • Figure 2 is a flowchart illustrating an automatic laser power adjustment method for a confocal endoscope according to an embodiment of this application.
  • FIG. 3 is a schematic diagram of an operator structure provided in an embodiment of this application.
  • FIG. 4 is a schematic diagram of another operator structure provided in an embodiment of this application.
  • FIG. 5 is a schematic diagram of another operator structure provided in an embodiment of this application.
  • Figure 6 is a schematic diagram of another operator structure provided in an embodiment of this application.
  • Figure 1 is a flowchart illustrating a laser power determination model construction method provided in an embodiment of this application. Specifically, it may include:
  • selected Different laser powers are used to construct a laser power set. .
  • N frames of image data were captured in an air environment to form an air environment image dataset.
  • step S120 Similar to step S120, but this time the probe is immersed in a sodium fluorescein solution of a reference concentration. Similarly, at K different laser powers... To capture N frames of images, a solution environment image dataset is created. .
  • the above-mentioned solution environment image dataset Based on the above-mentioned air environment image dataset, the above-mentioned solution environment image dataset, laser power set and preset curve fitting method, perform data fitting to obtain the above-mentioned laser power determination model, wherein the above-mentioned laser power determination model includes a first correspondence relationship and a second correspondence relationship, the above-mentioned first correspondence relationship is the correspondence relationship between air environment image data and the above-mentioned K different laser powers, and the above-mentioned second correspondence relationship is the correspondence relationship between solution environment image data and the above-mentioned K different laser powers.
  • a pre-defined curve fitting method is used for data analysis and fitting.
  • a laser power determination model is established, which includes two corresponding relationships:
  • the first correspondence f1 the relationship between air environment image data and different laser powers.
  • the second correspondence f2 the relationship between solution environment image data and different laser powers.
  • the method proposed in this application by precisely controlling laser power and automatically adjusting it according to different environments (air and fluorescent dye solution), ensures optimal image quality under various conditions.
  • This method effectively addresses individual differences and variations in fluorescent dye concentration, ensuring moderate brightness and contrast in the image, thus making it easier to identify details and lesions.
  • Automated laser power adjustment reduces the burden on physicians operating confocal endoscopes. Physicians do not need in-depth knowledge of how to adjust laser power based on images, reducing training requirements and minimizing human error during operation.
  • the model proposed in this application can be used to achieve automated laser power adjustment, shortening equipment adjustment time and accelerating the diagnostic process.
  • the model in this application can adapt to different types of confocal endoscopes and diverse clinical environments.
  • the model's versatility allows for easy integration into different hardware and software configurations, providing a wider range of applications.
  • this application achieves automatic laser power adjustment of confocal endoscopes in clinical use, effectively improving image quality and operational efficiency while reducing the complexity of physician operation and training requirements, providing a more efficient and accurate diagnostic tool for clinicians.
  • the above-mentioned data fitting based on the above-mentioned air environment image dataset, the above-mentioned solution environment image dataset, the laser power set, and the preset curve fitting method is used to obtain the above-mentioned laser power determination model, including:
  • the average brightness signal values at all fiber core locations under each laser power are used to construct a set of average fiber core brightness signals in the air.
  • the average brightness signal values at all fiber core locations under each laser power are used to construct a set of average fiber core brightness signals in solution.
  • Data fitting is performed based on the above-mentioned average value set of fiber core brightness signals in air, the above-mentioned laser power set, and the above-mentioned preset curve fitting method to construct the above-mentioned first correspondence relationship;
  • the data is fitted using the average set of fiber core brightness signals in the solution, the laser power set, and the preset curve fitting method to construct the second correspondence.
  • the laser power determination model is created.
  • the average image set of air at all laser powers can be obtained by taking the average value of pixel regions from the above air environment image dataset. and in The average value of the brightness signal at all fiber core locations is extracted and denoted as the set of average brightness signal values of the fiber core in air. ,in .
  • the mean image set of sodium fluorescein solution at all laser powers was obtained by taking the mean value of the solution environment image dataset. ;Depend on Extract the average value of the brightness signal at all fiber core locations to form a set of average brightness signal values of the fiber core in the solution. ,in .
  • f1 is the first correspondence.
  • f2 represents the second correspondence.
  • the laser power determination model is a model that includes the first correspondence and the second correspondence.
  • it also includes:
  • the fiber core is positioned to obtain its location.
  • the fiber core is located using the aforementioned air environment image dataset or the aforementioned solution environment image dataset.
  • an effective image set can be obtained using an air environment image dataset or the aforementioned solution environment image dataset. Then, the median value is calculated for these effective images pixel by pixel.
  • An effective image set refers to a collection of clear images selected from a large amount of imaging data through some filtering mechanism. This filtering aims to ensure the quality of the selected images, excluding blurry or damaged images. The purpose of calculating the median image is to reduce or eliminate random noise, accidental errors, or other one-off anomalies. Median filtering is a non-linear process that is particularly effective in preserving image edge and structural details. Based on the effective image set, a statistical method is used to calculate the cumulative probability of the fiber core's location.
  • the possible locations of the fiber core in each frame are scored or their probabilities evaluated, and these evaluation values are then accumulated to form an overall estimate of the actual location of the fiber core. This improves the accuracy and reliability of fiber core location identification.
  • an exclusion operation is performed to identify connected components in the image, i.e., regions formed by adjacent pixels. This includes removing pixels with probabilities below a certain threshold, retaining only high-probability regions. Identifying connected components effectively eliminates isolated noise points or non-target regions, focusing on the region most likely to be the fiber core.
  • one or more candidate fiber core locations are determined. This process involves analyzing the shape, size, and location of each connected region to determine which area most likely corresponds to the actual fiber core location.
  • the potential fiber core location area is narrowed down to more specific candidate locations, providing an accurate reference for the final fiber core localization.
  • Each candidate fiber core location undergoes further evaluation and processing, including assessing its accuracy and reliability, to ultimately determine the precise location of the fiber core.
  • Detailed evaluation of candidate locations ensures that the selected fiber core location is as accurate as possible.
  • image processing techniques such as edge detection and contrast enhancement, can also be used to improve the visual contrast between the fiber core and other parts of the fiber.
  • Image analysis algorithms such as pattern recognition or machine learning models, are used to identify and locate the precise location of the fiber core.
  • the methods for obtaining the average value of the brightness signal at the aforementioned fiber core location and the average value of the fiber core brightness signal in the solution are as follows:
  • the average of N frames of image data acquired at each laser power is calculated pixel by pixel to obtain the average image set in air.
  • Image set of mean values in solution
  • the average value set of fiber core brightness signal in the solution is extracted from the fiber core location located on the mean image set in the above solution.
  • the average value of the signal at all fiber cores is extracted using the above-mentioned fiber core positioning results, and denoted as .
  • the above reference concentration is the average core brightness signal in the reference solution.
  • the average brightness signal of the fiber core in the aforementioned reference solution is the average brightness signal of all fiber core positions extracted from the located fiber core position on the average image set in the reference solution.
  • the aforementioned average image set in the reference solution is obtained by averaging multiple frames of image data obtained by immersing the endoscope probe in the aforementioned reference concentration of fluorescein sodium solution at maximum laser power.
  • a sodium fluorescein solution of a certain concentration is prepared, and this concentration is denoted as...
  • Sodium fluorescein is a commonly used fluorescent dye that fluoresces under specific laser irradiation.
  • the endoscope probe is immersed in this solution and the laser power is adjusted to maximum to ensure that the acquired brightness signal value is within a preset range.
  • This preset range is set according to experimental or clinical needs to ensure image quality and safety.
  • the preset range can be... .
  • the brightness values in the preset range of the above brightness values are the maximum brightness values that the hardware can achieve, multiplied by a coefficient greater than or equal to 0.5 and less than or equal to 1.
  • the upper limit of the signal value is denoted as The ideal signal value is
  • the acceptable signal value range is Maximum laser power Minimum laser power , This represents the current laser power.
  • the maximum brightness value that can be achieved is determined by hardware characteristics (such as the number of bits in the AD sampling chip).
  • Typical values are as follows: Take 0.9, Take 0.85, Take 0.95.
  • the aforementioned preset curve fitting methods include one or more of the following: straight line fitting, piecewise straight line fitting, quadratic equation, multivariate equation, and log curve.
  • pre-defined curve fitting methods are a key step in establishing a model for determining laser power. These methods model the relationship between image data and laser power, thereby providing optimal laser power settings for the endoscope.
  • curve fitting methods include linear fitting, piecewise linear fitting, quadratic equations, polynomial equations, and logarithmic curves.
  • the brightness signal value of the fiber core containing the current concentration of sodium fluorescein solution is first measured using a confocal endoscope.
  • This brightness signal value reflects the luminescence intensity of sodium fluorescein under specific laser excitation.
  • a previously established laser power determination model is used, which is based on standard data of sodium fluorescein solutions at different concentrations. The model consists of two main parts: a first correspondence (the relationship between sodium fluorescein concentration and brightness) and a second correspondence (the relationship between brightness and laser power).
  • a model is constructed that describes the relationship between core brightness and laser power at the current concentration.
  • This model allows for dynamic adjustment of the laser power based on the actually measured brightness signal value.
  • the constructed model is used to determine the laser power corresponding to the current sodium fluorescein solution concentration when the core brightness signal just reaches the maximum brightness value achievable by the hardware. This automatic adjustment ensures optimal imaging results at different concentrations, preventing excessive or insufficient laser output.
  • the method proposed in this application maximizes image quality and improves diagnostic accuracy and efficiency by precisely adjusting the laser power. It prevents sample damage or equipment failure due to excessive laser power, while also avoiding image information loss due to insufficient brightness.
  • This automatic adjustment method reduces the operator's workload, making the operation of confocal endoscopes simpler and safer, especially in complex or lengthy medical examinations.
  • the construction of a model of the current concentration, laser power, and fiber core brightness to determine the laser power corresponding to the current concentration of sodium fluorescein solution when the fiber core brightness signal just reaches the maximum brightness value achievable by the hardware specifically includes:
  • the brightness signal value adjustment range is determined based on the maximum brightness value that the hardware can achieve, the first adjustment coefficient, and the second adjustment coefficient; the laser power adjustment range is determined based on the maximum laser power and the minimum laser power of the laser.
  • a brightness signal value adjustment range is determined based on a set upper limit for the brightness signal value and the first and second adjustment coefficients. This range serves as a reference for adjusting the laser power in subsequent steps, ensuring that the image brightness signal intensity is within an ideal range, neither too bright nor too dark.
  • the upper limit of the signal value is denoted as The ideal signal value is .
  • the acceptable signal value range is Maximum laser power Minimum laser power , This represents the current laser power.
  • the maximum brightness value that can be achieved is determined by hardware characteristics (such as the number of bits in the AD sampling chip). and It is determined by the laser itself, specifically the maximum and minimum laser power that the laser can provide.
  • the effective image set is obtained by using the maximum laser power as the initial laser power
  • image acquisition is performed using the endoscope's current maximum laser power to obtain a set of buffered images, with a frame rate of [number missing].
  • the cached image set be . These images will be used for subsequent analysis and processing to evaluate image quality at maximum power and provide preliminary data for power adjustment.
  • the initially obtained cached image set is filtered to remove images of low quality or those that do not meet analytical requirements. Valid images are then selected from the cached images. Due to the inherent characteristics of confocal endoscopy—small field of view, high magnification, and short working distance—a portion of the images produced are invalid, such as completely black images when there is no tissue contact, completely white images when contact is too tight, and motion artifacts. Ignoring these images when calculating the laser power to be adjusted results in more accurate values, closer to the expected value.
  • the filtered image set contains more representative and analytically valuable images for further brightness analysis.
  • the current concentration of the sodium fluorescein solution corresponding to the current laser power is calculated based on the average of the larger brightness values.
  • an adjusted target laser power is calculated based on the larger brightness values extracted from the selected image set and a previously set brightness signal value adjustment range. This new laser power keeps the image brightness within an ideal range, improving the image's usability and diagnostic value.
  • the larger value can be obtained by extracting all fiber core brightness signal values from the image, calculating the histogram, and taking a certain percentage of values accumulated from high to low in the histogram as the larger brightness value, denoted as . A certain percentage can be taken as 5%. The average of the larger brightness values for each frame in the selected image set is then calculated. .
  • the laser power determination model is constructed based on the concentration of sodium fluorescein solution, the brightness signal value of the fiber core, and the laser power.
  • the laser power at which the maximum brightness value that the hardware can just reach is calculated based on the current concentration of sodium fluorescein solution.
  • the laser power needs to be increased. If the laser power has not reached its maximum value, it can be increased. First, the current concentration of the sodium fluorescein solution needs to be determined. Then, using either of the laser power determination models mentioned above or the current concentration of the sodium fluorescein solution, the laser power required to reach the maximum brightness signal can be calculated.
  • the laser power at which the brightness signal reaches its maximum value is determined as the adjusted target laser power.
  • the current concentration of the sodium fluorescein solution corresponding to the current laser power is calculated based on the average of the larger brightness values mentioned above, including:
  • the current concentration of sodium fluorescein solution corresponding to the current laser power is calculated.
  • the concentration of sodium fluorescein was calculated using the established model. Just reached the maximum value of the brightness signal laser power at time : ;
  • the methods described above for obtaining a valid set of images include:
  • the cached images in the cached image set are filtered to obtain the effective image set.
  • effective image screening can be performed based on the following methods:
  • Filtering operations can specifically include:
  • the method for calculating the larger brightness value is as follows: extract all fiber core brightness signal values from the image, calculate the histogram, and take the values that account for the largest percentage from high to low in the histogram as the larger brightness value, denoted as . .
  • the percentages from highest to lowest are as follows:
  • the proportion of values between 9 and 8 is less than 5%, while the proportion of values between 9 and 7 is greater than 5%. Therefore, the largest brightness signal value with a cumulative proportion of 5% from high to low is 7.
  • the method for calculating larger gradient values is as follows: convolve the image using the following four 3x3 operators respectively, and obtain... , , , .make
  • the histogram is used to select the values that represent the largest gradient, with the cumulative percentage from high to low in the histogram being 5%.
  • the operators used can be any four of those shown in Figures 3 to 6.
  • the operators used can also be symmetrically flipped along the row, column, and diagonal where 0 is located.
  • the laser power determination model construction method provided in this application through precise control of laser power, automatically adjusts the laser power according to different environments (air and fluorescent dye solution) to ensure optimal image quality under various conditions.
  • This method can effectively cope with individual differences and variations in fluorescent dye concentration, ensuring moderate brightness and contrast in the image, thus making it easier to identify details and lesions.
  • Another embodiment of this model construction method implements an automatic laser power adjustment method, which can automatically adjust to the optimal laser output, thereby improving image quality, simplifying the operation process, and reducing the burden on doctors during operation. Therefore, the laser power determination model construction method and the automatic laser power adjustment method provided in the various embodiments of this application have industrial applicability.

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Abstract

La présente demande se rapporte au domaine de l'imagerie endoscopique, et concerne un procédé de construction de modèle de détermination de puissance de laser, et un procédé de réglage automatique de puissance de laser. Le procédé de construction de modèle de détermination de puissance laser consiste à : effectuer un ajustement de données sur la base d'un ensemble de données d'image d'environnement dans l'air, d'un ensemble de données d'image d'environnement en solution, d'un ensemble de puissances de laser et d'un procédé d'ajustement de courbe prédéfini, de façon à obtenir un modèle de détermination de puissance de laser. L'invention concerne également un procédé de réglage automatique de puissance de laser, mis en œuvre au moyen du modèle de détermination de puissance de laser.
PCT/CN2025/100098 2024-06-28 2025-06-10 Procédé de construction de modèle de détermination de puissance de laser et procédé de réglage automatique de puissance de laser Pending WO2026001663A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
CN202410852246.5A CN118736350A (zh) 2024-06-28 2024-06-28 一种激光功率确定模型构建方法、调节方法及存储介质
CN202410852114.2A CN118717002A (zh) 2024-06-28 2024-06-28 一种共聚焦内窥镜激光功率自动调节方法
CN202410852114.2 2024-06-28
CN202410852246.5 2024-06-28

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