Ocular corneal treatment system based on near-infrared light recognition

Abstract

The present application relates to the field of ophthalmic medical technology, especially to an eyeball cornea treatment system based on near-infrared light recognition, which acquires optical information of eyeball cornea and choroid by collecting near-infrared light signals, and performs digitalization and filtering processing on the original image to output processed image data. Combining edge detection and threshold segmentation, choroid defects or atrophic lesion points are identified, and corneal thickness and curvature are measured to determine the energy intensity, irradiation time, wavelength and focusing position of the excimer light beam. According to the parameters, an excimer light beam with a wavelength of 248 nanometers is emitted to irradiate and treat the lesion area, which improves the positioning accuracy of the lesion while avoiding damage to normal tissue structures, and meets the safety and effectiveness requirements of eye treatment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ophthalmic medical technology, and particularly to an eyeball cornea treatment system based on near-infrared light recognition. BACKGROUND

[0002] Early diagnosis and treatment of eyeball cornea diseases are of great significance for maintaining visual health. The existing technology mainly adopts direct naked-eye observation and traditional white light examination methods, and laser treatment devices relying on rough parameter regulation, which has limited image acquisition resolution, inaccurate lesion area positioning, and uncertain laser parameter adjustment, which may cause damage to normal tissues, reduce treatment safety and effectiveness. SUMMARY

[0003] In view of the above problems existing in the prior art, the present application provides an eyeball cornea treatment system based on near-infrared light recognition. The present application uses near-infrared light to collect eyeball cornea and choroid images, and realizes accurate positioning of the lesion area after digitalization and filtering processing using edge detection and region segmentation technology. Based on the corneal thickness and curvature, the emission parameters of the excimer light beam are determined, and the lesion site is irradiated with a wavelength of 248 nanometers laser to protect the normal tissue while ensuring the treatment effect and improve the treatment safety.

[0004] As shown in Figure 2 A kind of eyeball cornea treatment system based on near-infrared light recognition, comprising:

[0005] A near-infrared light acquisition module for acquiring optical signals of eyeball cornea and choroid and generating initial images;

[0006] An image processing module for digitalizing and filtering processing the initial images, and outputting processed image data;

[0007] A lesion detection module for identifying choroid defect or atrophy lesion points from the processed image data and generating positioning information;

[0008] A parameter determination module for determining the emission parameters of the excimer light beam according to the corneal thickness and curvature and the choroid image data, the emission parameters including energy intensity, irradiation time, wavelength and focusing position;

[0009] A light beam emission module for outputting excimer light beams with a wavelength of 248 nanometers according to the emission parameters to irradiate and treat the lesion points.

[0010] Preferably, the near-infrared light acquisition module acquires optical signals of eyeball cornea and choroid within a frequency range of 26.565~27.405MHz.

[0011] Preferably, the image processing module performs analog-digital conversion on the initial image and removes noise by using frequency domain filtering to obtain processed image data.

[0012] Preferably, the lesion detection module extracts the outline of the eyeball tissue based on a gradient operator and identifies the boundary of the choroid defect or atrophic lesion point by using threshold segmentation.

[0013] Preferably, the parameter determination module obtains corneal thickness and curvature data by emitting and receiving near-infrared light at at least two different angles and performing numerical inversion, and then determines the emission parameters of the excimer light beam in combination with the choroid image data.

[0014] Preferably, the energy intensity is set by grading according to the corneal thickness measurement, and the ratio of the lesion area to the reference area is regulated by combining the lesion depth and the logarithmic function operation. When the lesion area is lower than the reference area, the logarithmic term is negative to reduce the energy output, and when the calculated value is lower than the minimum energy threshold, the minimum energy threshold is used as the final output. The irradiation time is set by segmenting according to the degree of the lesion, the wavelength is selected in combination with the optical absorption coefficient of the choroid, and the focusing position is calibrated according to the coordinates of the lesion area.

[0015] Preferably, the excimer light beam output by the light beam emission module has a power intensity of not more than 1 mW / cm2 and can work continuously for not less than one hour.

[0016] Preferably, the light beam emission module periodically monitors the choroid reflection signal during the irradiation process and compares it with the power deviation threshold. When the power deviation exceeds the threshold, the light beam emission is stopped and an alarm signal is output.

[0017] Preferably, the light beam emission module includes a short circuit detection device that immediately cuts off the power supply when the current exceeds a preset safety threshold and records fault information.

[0018] Preferably, the image processing module and the lesion detection module transmit processed image data through a data bus, and the parameter determination module and the light beam emission module are cooperatively scheduled through control signals.

[0019] Compared with the prior art, the advantages and beneficial effects of the present application are:

[0020] By using near-infrared image recognition technology to collect high-quality images of the cornea and choroid of the eyeball, and using edge detection and region segmentation methods to accurately locate the lesion area, and by determining the emission parameters of the excimer light beam based on the corneal thickness and curvature data, the effect of precise irradiation of the lesion area is achieved, while effectively protecting the normal tissue, significantly improving the safety and reliability of the treatment. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1A schematic diagram of the near-infrared light image recognition principle in the present application is shown in the figure.

[0022] Figure 2 A structural block diagram of the system of the present application is shown in the figure. DETAILED DESCRIPTION

[0023] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood, however, that the description is merely exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. However, it would be apparent that one or more embodiments can be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques have been omitted to avoid unnecessarily obscuring the concept of the present disclosure.

[0024] The terms used herein are merely used to describe specific embodiments and are not intended to limit the present disclosure. The terms "include", "comprise" and the like used herein indicate the presence of the described features, steps, operations and / or components, but do not exclude the presence or addition of one or more other features, steps, operations or components.

[0025] All terms used herein (including technical and scientific terms) have meanings commonly understood by one of ordinary skill in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted in a manner consistent with the context of the present specification, and should not be interpreted in an idealized or overly formal manner.

[0026] The near-infrared light image recognition technology is an inspection method that generates images and performs recognition using near-infrared light technology. When the electrons in the near-infrared light emitter are accelerated or oscillated, continuous or intermittent near-infrared light is generated in a specific direction. When near-infrared light of a specific wavelength is irradiated to the eyeball, it penetrates through transparent tissues such as the cornea and the lens to reach the choroid of the fundus. The vascular network and other tissue structures of the choroid of the fundus reflect, scatter or absorb these near-infrared lights. When the near-infrared light encounters the choroid of the fundus, it reflects the carrier information representing the refractive index information. Finally, through digital-to-analog conversion and modulation demodulation mechanisms, the near-infrared light image formed by the amplification mechanisms such as automatic gain control is obtained, and the abnormal area is recognized.

[0027] As Figure 1As shown, the near-infrared light image recognition technology is an inspection method that generates images and performs recognition using near-infrared light technology. When the electrons in the near-infrared light emitter are accelerated or oscillated, continuous or intermittent near-infrared light is generated in a specific direction. When near-infrared light of a specific wavelength is irradiated to the eyeball, it penetrates through transparent tissues such as the cornea and the lens and reaches the choroid of the fundus. The vascular network and other tissue structures of the choroid of the fundus reflect, scatter, or absorb the near-infrared light. The reflected carrier information carrying refractive index information is encountered when the near-infrared light encounters the choroid of the fundus of the eyeball. Finally, the near-infrared light image formed through the analog-to-digital conversion and modulation demodulation and other mechanisms of the amplification mechanism such as the gain is obtained, and the abnormal area is recognized.

[0028] In clinical practice, doctors use a near-infrared light emitting probe to place it on the patient's eye and then emit near-infrared light. The near-infrared light is attenuated to different degrees when passing through the retinal pigment epithelial layer of the human eye. Therefore, when it encounters choroids of different thicknesses of the fundus of the eyeball, it reflects and returns to the probe. The reflected signal received by the near-infrared light probe is recorded and converted into an image. By measuring the intensity and time difference of the near-infrared light reflection, different images can be generated. These images can help doctors understand the problems of the choroid of the fundus of the patient's eye and help locate the choroidal defects or atrophic lesion points.

[0029] In the present application, the following steps are used to collect signals, digital conversion, filtering, image reconstruction, and abnormal area positioning after the near-infrared light penetrates through the transparent tissues of the eye:

[0030] First, the near-infrared light is emitted by the emitter to irradiate the eye tissue, and the receiver captures the penetrated signal and converts it into an electrical signal (the near-infrared light recognition working frequency band is shown in Table 1); then, the analog-to-digital converter (ADC) digitizes the analog signal, ensuring that the sampling frequency and quantization accuracy meet the requirements. Next, noise is removed through digital filtering technology to improve signal quality. The filtered signal generates a two-dimensional or three-dimensional image of the eye tissue using image reconstruction algorithms. Finally, the abnormal area (such as corneal lesions or lens opacity) is located through edge detection, region segmentation, feature extraction, and machine learning methods. First, the Canny, Sobel, and other edge detection algorithms are used to extract the contour information of the eye structure, and the image is divided into corneal, lens, and other regions through threshold segmentation, region growing, or deep learning segmentation network. Next, texture, shape, color, and other features are extracted from the segmented regions to distinguish normal and abnormal areas. Then, support vector machines, random forests, or deep learning classifiers are used to classify the regions to determine whether there are abnormalities. Finally, the target detection algorithm is directly used to accurately locate the abnormal area. This provides accurate basis for the early diagnosis and treatment of eye diseases. This process combines the characteristics of near-infrared light and advanced signal processing technology to achieve non-invasive eye tissue detection and analysis.

[0031] Table 1

[0032]

[0033] The excimer beam is a 248nm light beam generated by the transition of molecules of a mixed gas of inert gas and halogen gas excited by an excimer beam generator, and has strong penetration, strong directivity and large output power. The excimer beam mainly irradiates biological tissues to produce benign biological stimulation and photochemical effect, stimulates the peripheral nerve receptors and peripheral blood vessels of the eye, effectively improves the blood circulation and nerve regulation around the fundus, improves the blood circulation and metabolism of the fundus tissue, restores the physiological regulation function of the choroid of the fundus, and achieves the purpose of correcting and relieving hyperopia or astigmatism. The retinal blood vessel density is compared as shown in Table 2.

[0034] Table 2

[0035]

[0036] Among them, compared with the mild myopia group, P<0.05; compared with the moderate myopia group, P<0.05; compared with the high myopia group, P<0.05.

[0037] The present application combines near-infrared image recognition with excimer light beam, can identify and treat various eye diseases, through near-infrared image recognition technology, obtains the corneal thickness, curvature and detailed data of choroid of the patient's eyeball, and these data are used to determine the energy intensity, irradiation time, wavelength and focusing position of the excimer light beam, so as to ensure that the light beam can accurately act on the target area, and at the same time avoid damage to healthy tissues. The excimer light beam stimulates the peripheral nerve receptors and peripheral blood vessels of the eye, effectively improves the blood circulation and nerve regulation around the eye, improves the blood circulation and metabolism of the eye tissue, restores the physiological regulation function of the choroid of the fundus, and combines the high precision and controllability of the excimer light beam with the accurate navigation of the near-infrared image recognition to treat myopia and reduce the risk of complications such as dry eye and glare. The control details of the excimer light beam are as follows:

[0038] 1. Energy intensity regulation: adjust the energy intensity of the light beam according to the corneal thickness and lesion depth.

[0039]

[0040] Among them refers to the reference area. When , it means that the lesion area is less than the reference value, and the system needs to reduce the energy intensity. Small area lesion needs more concentrated low energy stimulation to avoid excessive treatment and damage to surrounding healthy tissues. The negative value is essentially a reverse regulation of energy compensation. is a depth dominant term, determines the energy baseline value, and reflects the core influence of lesion depth on energy penetration. is the area correction term, which fine-tunes the energy demand based on the lesion area on the depth basis (large area needs energy dispersion, small area needs energy concentration). represents the depth coefficient: converting physical depth into energy demand, reflecting the optical properties of the tissue. The effective treatment energy threshold at different depths is measured by ex vivo tissue experiments, and the data is fitted to obtain the slope . represents the depth: directly quantifying the vertical position of the lesion, which is the core input of energy regulation. The two constitute the linear main body of the formula, ensuring that the energy monotonically increases with the depth, providing a benchmark reference for the logarithmic term, and the staff can adjust to adapt to the light transmittance of different patient tissues to achieve personalized treatment.

[0041] Synergistic relationship with other parameters: (1) If is large (depth sensitive), the area correction term needs to be appropriately reduced to avoid excessive dependence of energy on area. (2) b affects the sensitivity of the area term, which needs to be calibrated with to ensure that the weights of depth and area are reasonable.

[0042] Generally , therefore the negative value of the logarithmic term will reduce the total energy , which conforms to the clinical logic that small lesion area needs low energy. The invention limits the base , ensuring monotonically increasing, which conforms to the clinical logic. When the result is greater than 0, it represents a positive increase in energy; when the result is less than 0, the energy has a negative feedback, thereby satisfying .

[0043] Processing in actual application: considering that cannot output negative values, the invention sets a minimum energy threshold to ensure that negative values will not result in non-physical energy output:

[0044]

[0045] For example: set the reference area , the lesion area , : set = 5 mJ / mm 2 , then the logarithmic term contribution is 5 × (−1) = −5 mJ / mm 2 , indicating that the energy needs to be reduced by 5 mJ / mm 2 to avoid over-treatment.

[0046] In the invention, to ensure that the unit of is mJ / mm 2 and the unit of is mm, The unit must be:

[0047]

[0048] in, Energy density absorbed per unit volume of tissue (mJ / mm²) 3 This reflects the rate of energy decay along the depth direction. The logarithmic terms are dimensionless, therefore... The unit needs to cooperate with Same, i.e., mJ / mm 2 .

[0049] 2. Irradiation time adjustment: Adjust the irradiation time according to the type of lesion and nerve sensitivity.

[0050]

[0051] in This refers to the irradiation time; This represents the nerve sensitivity coefficient. As a weighting factor for lesion type; The energy intensity of the beam.

[0052] 3. Wavelength Selection: The system selects the most effective wavelength based on the optical characteristics of the lesion area (such as absorption spectrum). For example, corneal lesions may be more sensitive to a specific wavelength of light, and the system will automatically select the optimal wavelength based on patient data.

[0053] 4. Focus Position Adjustment: The focus point of the beam is adjusted according to the location and depth of the lesion area. The focus position of the beam is dynamically calibrated through real-time image processing and patient data.

[0054] Near-infrared light image recognition technology replaces traditional eye examination methods. Its non-contact and non-invasive nature completely avoids direct contact with the patient's eyes, thus reducing discomfort and potential infection risks. Near-infrared light image recognition technology can more quickly capture and analyze choroidal images of the fundus. Compared to traditional methods, this invention more quickly and accurately identifies and locates choroidal defects or atrophic lesions.

[0055] The choroid defect or atrophic lesion point information is identified and positioned by near-infrared light images, wherein the near-infrared light images can effectively identify and position the choroid defect or atrophic lesion point information by the deep tissue penetration ability and high contrast imaging characteristics, combined with image processing, feature extraction and machine learning technology. First, the image is preprocessed by denoising, contrast enhancement and registration, then the choroid region is segmented by edge detection, and the texture, shape and intensity features are extracted. Then, the machine learning is used to identify the lesion area, and the edge detection, target detection algorithm or heat map generation technology is used to accurately position the lesion point. Finally, the results are optimized by morphological operation and connected region analysis, and the final output is the bounding box and center point coordinates of the lesion area, which are transmitted into the product to analyze the lesion point and control the excimer beam to manufacture the excimer beam. The excimer beam provides very accurate energy deposition to stimulate the choroid peripheral nerve receptors and terminal blood vessels, ensuring that the choroid defect or atrophic lesion point area receives treatment, thereby minimizing damage to the surrounding healthy choroid tissue, and thus playing a therapeutic role. The mean axial length of adolescents of different ages before and after treatment is shown in Table 3.

[0056] Table 3

[0057]

[0058] The method of stimulating the eye by the excimer beam in the application can relieve eye muscle fatigue, reduce muscle spasm, and improve blood circulation. At the same time, biological stimulation is generated inside the eye tissue, and the choroid of the fundus is repaired. The excimer beam penetrates deep into the eye tissue, which can produce biological heat effect and does not damage the normal biological tissue of the human body, which meets the basic concept of the project.

[0059] The integrated architecture of the system includes:

[0060] The near-infrared light image acquisition and processing module acquires images of the cornea and choroid of the eyeball by near-infrared light, and digitizes and filters the acquired image signals to generate processed image data;

[0061] The image analysis module performs edge detection and region segmentation on the processed image data to identify the choroid defect or atrophic lesion point and output the positioning information;

[0062] The emission parameter determination module determines the emission parameters of the excimer beam according to the corneal thickness, curvature and choroid image data, and the emission parameters include energy intensity, irradiation time, wavelength and focusing position;

[0063] The excimer beam emission module emits the excimer beam with a wavelength of 248 nanometers according to the emission parameters to irradiate the lesion point for treatment;

[0064] The communication control unit is used to realize data transmission and cooperation between modules.

[0065] CAN bus or SPI protocol is used for communication between modules, and unified frame structure is used for data interaction to ensure stability and real-time performance of transmission. The transmission parameter determination module serves as the core to coordinate the work of each module: based on the determined transmission parameters, the parameters are distributed to the excimer beam emission module for execution of treatment, while interacting with the image analysis module to adjust the emission parameters of the excimer beam according to the eye tissue image; the battery charging and voltage stabilizing module monitors the power supply state in real time to ensure stable operation of the device; the application further includes an alarm prompt module to issue a warning and record a log in abnormal conditions (such as laser failure or low battery level). The overall architecture is divided into a hardware layer, a control layer and an application layer, the hardware layer is connected through standardized interfaces, the control layer runs a real-time operating system (RTOS) to ensure task scheduling, and the application layer provides a user interface and algorithm support. This layered design and modular cooperation ensure the efficiency, stability and precision of the device, providing reliable technical support for eye treatment.

[0066] The excimer beam emitter power is an important parameter of the excimer laser beam eye training instrument. Each country has a limit on the maximum emission power: the maximum in China and European countries is not more than 1mW / cm 2 ; the maximum power in North America is not more than 1.2mW / cm 2 ; and the maximum power in Japan is not more than 1.1mW / cm 2 dBm. For example, in actual application, considering the shortest distance between the excimer laser beam eye training instrument and the human eye as a whole, the excimer beam emitter power of 0.8mW / cm 2 is adjusted to maximize the prevention and treatment efficiency without harming the human eye.

[0067] The continuous working time of the excimer laser beam eye training instrument under normal working condition should be not less than 1 hour.

[0068] The excimer laser beam eye training instrument mainly uses near-infrared light in the ISM band between 26.565-27.405MHz. This band of near-infrared light has good penetration and can distinguish and distinguish different reflections from different objects, and is widely used in medical field.

[0069] The wavelength of the excimer beam is an important parameter of the excimer laser beam eye training instrument. The excimer laser beam eye training instrument uses an excimer beam with a wavelength of 248nm, which has strong penetration ability and does not harm human tissues, and the excimer beam has good therapeutic effect on choroid.

[0070] Based on the demand analysis of the user, the excimer laser beam eye training instrument of the application is integrated with treatment, image recognition, intelligent control and the like by excimer light beam technology, near-infrared light image recognition technology and ATmega328P single-chip microcomputer control technology.

[0071] The application emits near-infrared light to the eye through the transmitter, when the near-infrared light meets the choroid of the fundus of the eyeball, reflection, scattering, transmission and the like occur, the receiver receives the electromagnetic wave after the target action, and processes and analyzes the received signal, reconstructs the image of the choroid of the fundus of the eyeball, and further identifies the choroid defect or atrophy lesion point.

[0072] In the practical application, the biological tissue is not only not damaged, but also has the repairing and blood-activating effects, so that biological stimulation is generated in the internal eye tissue, the local blood circulation is improved, and the lesion tissue of the choroid of the fundus of the eye is promoted to restore to the normal state.

[0073] Those skilled in the art should understand that the embodiments of the application can be provided as a method, a system or a computer program product.

[0074] The above is only an embodiment of the application, and is not used to limit the application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the application should be included in the scope of the claims of the application.

Claims

1. An eye cornea treatment system based on near-infrared light recognition, characterized in that, The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module.

2. The eye cornea treatment system based on near-infrared light recognition according to claim 1, characterized in that, The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module.

3. The eye cornea treatment system based on near-infrared light recognition according to claim 1, characterized in that, The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module.

4. The eye cornea treatment system based on near-infrared light recognition according to claim 1, characterized in that, The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module.

5. The eye cornea treatment system based on near-infrared light recognition according to claim 1, characterized in that, The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module.

6. The eye cornea treatment system based on near-infrared light recognition according to claim 1, characterized in that, The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module.

7. The eye cornea treatment system based on near-infrared light recognition according to claim 1, characterized in that, The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module.

8. The eye cornea treatment system based on near-infrared light recognition according to claim 1, characterized in that, The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. The application relates to a near-infrared light acquisition module, an image processing module, a lesion detection module, a parameter determination module and a light beam emission module. 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