CN117462073B - Hand-held polarization imaging intraocular pressure detection device and method - Google Patents
Hand-held polarization imaging intraocular pressure detection device and method Download PDFInfo
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- A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
- A61B3/16—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for measuring intraocular pressure, e.g. tonometers
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- G02B27/286—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00 for polarising for controlling or changing the state of polarisation, e.g. transforming one polarisation state into another
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Abstract
The invention relates to a hand-held polarized imaging intraocular pressure detection device and a method, wherein the device comprises the following components: a light source for generating illumination light; a polarizing element for converting illumination light into linearly polarized light of a high extinction ratio; the phase modulator is used for converting the linearly polarized light into circularly polarized light and guiding the circularly polarized light to the cornea region of the human eye to be detected so as to be reflected by the cornea region of the human eye to be detected; the conversion module is used for converting the signal light reflected by the cornea region of the human eye to be detected into linearly polarized light; the imaging detection module is used for acquiring the image information of the cornea region of the human eye to be detected; the image analysis module is embedded with an intraocular pressure deep learning model and is used for collecting cornea region image information output by the imaging detection module and calling the intraocular pressure deep learning model to obtain an intraocular pressure measurement result of a tested person according to the cornea region image information output by the imaging detection module; the method is based on the device; the invention can realize that the tested person is not hurt in the process of accurately obtaining the intraocular pressure result.
Description
Technical Field
The invention relates to the field of optical instruments, in particular to a handheld polarized imaging intraocular pressure detection device and method.
Background
Vision health is an important component of national health, relates to the whole life cycle of people in all ages, and is a major public health problem and a social problem related to folk life.
Intraocular pressure measurements play a vital role in assessing eye health and detecting eye disease in ophthalmic examinations, particularly in the early diagnosis of glaucoma. Glaucoma is the second leading cause of blindness worldwide, often accompanied by elevated intraocular pressure, and early diagnosis and treatment is critical to alleviating the disease. The existing intraocular pressure detection methods mainly comprise the following two methods: the first is applanation tonometer measurement, which is based on the principle of static equilibrium, the cornea is applanated by a metal probe with a plane end surface, the force born by the metal probe is recorded when the metal probe reaches stress balance, and the measurement value of the intraocular pressure is obtained according to the definition of the pressure. However, this method and the corresponding apparatus generally require local anesthesia or the like to be performed on the patient in order not to cause stress reaction to the patient during use. The second method is based on the hydrodynamic balance principle and adopts a pneumatic non-contact tonometer for measurement, wherein the method comprises the steps of spraying an airflow with gradually increased speed to the surface of the cornea, flattening the cornea when the airflow speed reaches a certain degree, calculating the force exerted by the airflow on the surface of the cornea by recording the airflow speed at the moment, and obtaining the intraocular pressure measurement value according to the definition of the pressure. Although non-contact measurement is realized in this way, the method has larger errors for the estimation of the airflow speed, the estimation of the flattening area and the like, and therefore, the measurement method has larger errors.
In summary, the existing intraocular pressure measurement methods, such as applanation tonometer and pneumatic tonometer, have the problems of complex process, low precision, easy discomfort and the like, and metal or gas is needed to be used for applanation of cornea in the detection process, so that the operation is inconvenient (especially for children) in the use process, and meanwhile, larger measurement errors exist in the measurement process, which makes the early screening of glaucoma and the timely adjustment of treatment scheme challenging.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a handheld polarized imaging intraocular pressure detection device and method which are harmless to a tester.
The invention provides a handheld polarized imaging intraocular pressure detection device, which has the following technical scheme:
a hand-held polarization imaging intraocular pressure detection device, comprising:
A light source for generating illumination light;
A polarizing element for converting the illumination light into linearly polarized light having a extinction ratio of not less than 1000:1;
A phase modulator for converting the linearly polarized light into circularly polarized light and guiding the circularly polarized light to a cornea region of the human eye to be measured so as to be reflected by the cornea region of the human eye to be measured;
the conversion module is used for converting the signal light reflected by the cornea region of the tested human eye into linearly polarized light;
the imaging detection module is used for acquiring the image information of the cornea region of the detected human eye;
The image analysis module is embedded with an intraocular pressure depth learning model and is used for collecting cornea region image information output by the imaging detection module and calling the intraocular pressure depth learning model to obtain an intraocular pressure measurement result of a tested person according to the cornea region image information output by the imaging detection module;
wherein,
The polarization element and the phase modulator are sequentially arranged along the propagation direction of illumination light, the conversion module and the imaging detection module are sequentially arranged along the propagation direction of signal light reflected by the cornea region of the human eye to be detected, and the image analysis module is electrically connected with the imaging detection module.
The device provided by the invention comprises a light source, a polarizing element, a phase modulator, a conversion module, an imaging detection module and an image analysis module, wherein the polarizing element and the phase modulator are sequentially arranged along the propagation direction of illumination light, the conversion module and the imaging detection module are arranged along the propagation direction of signal light reflected by the cornea region of the human eye to be detected, the image analysis module is electrically connected with the imaging detection module, and further, after the illumination light is emitted by the light source, the light source is converted into linear polarized light with the extinction ratio not lower than 1000:1 by the polarizing element, the linear polarized light is modulated by the phase modulator to form circularly polarized light and is led to the cornea region of the human eye to be detected, the reflected signal light is formed into linear polarized light after the cornea region of the human eye to be detected is reflected by the conversion module, and then enters the imaging detection module, the imaging detection module acquires the image information of the cornea region of the human eye to be detected, and the image analysis module can enter the image analysis module, and after the image analysis module acquires the image information of the cornea region, the intraocular pressure depth learning model is called according to the image information of the cornea region output by the imaging detection module, and the measured result of the human eye intraocular pressure is obtained.
The device provided by the invention realizes non-contact, noninductive, rapid and accurate measurement of intraocular pressure through polarization imaging of a cornea region or surface based on an optical measurement principle, thereby reducing inconvenience in inspection and measurement errors, avoiding physiological damage to a tested person, avoiding discomfort to a patient, helping doctors to discover glaucoma and other eye diseases earlier, adopting timely treatment measures, and reducing pain and medical cost of the patient. Meanwhile, as the intraocular pressure deep learning model is embedded in the image analysis module, compared with the mechanical measurement method in the prior art, the measurement error can be reduced, and the measurement precision is improved.
The device provided by the invention adopts an advanced automatic control system, has the advantages of simple and convenient operation and can rapidly and accurately finish intraocular pressure measurement. Can be widely applied to places such as hospitals, clinics, pharmacies and the like, is convenient for medical staff to use, improves diagnosis and treatment efficiency, and has wide applicable crowd including special crowd such as children, old people and the like, so that the requirements of different patients can be better met.
Preferably, the polarizing element is an annular linear polarizer; and further, the extinction ratio can be controlled, so that the extinction ratio is not lower than 1000:1 when natural light is converted into linearly polarized light.
Preferably, the phase modulator is an annular lambda/4 wave plate so as to ensure that linearly polarized light is smoothly converted into circularly polarized light and is guided to the cornea region of the human eye to be detected so as to be reflected by the cornea region of the human eye to be detected, and the phase modulator has low cost and small occupied space region.
Preferably, the conversion module includes, in order along a propagation direction of the signal light reflected by the cornea region of the human eye to be tested:
The circular lambda/4 wave plate is used for carrying out phase delay modulation on the signal light reflected by the cornea region of the tested human eye;
The circular linear polaroid is used for converting the light output by the circular lambda/4 wave plate into linearly polarized light;
furthermore, the signal light reflected by the cornea region of the tested human eye can sequentially pass through the circular lambda/4 wave plate and the circular linear polaroid, and can be converted into linear polarized light again, and meanwhile, information loss is avoided.
Preferably, the polarization direction of the circular λ/4 plate is opposite to the polarization direction of the phase modulator, and the polarization direction of the circular linear polarizer is orthogonal to the polarization direction of the polarizing element; thereby ensuring accurate phase delay modulation and polarization signal conversion of the reflected light from the cornea region.
Preferably, the imaging detection module includes, in order along a propagation direction of the signal light reflected by the cornea region of the human eye to be detected:
The imaging lens is used for imaging the cornea region of the human eye to be tested to form an image of the cornea region of the human eye to be tested;
The photoelectric detector is used for receiving the cornea region image of the human eye to be detected and converting the cornea region image of the human eye to be detected into an electric signal of the cornea region image of the human eye to be detected;
wherein,
The photoelectric detector is electrically connected with the image analysis module;
When the signal light reflected by the cornea region of the human eye to be detected is transmitted to the imaging lens, the signal light can be focused into a clear image containing the cornea region of the human eye to be detected, namely, the cornea region image of the human eye to be detected, the image can be accepted by the photoelectric detector and is regulated into an electric signal to be output to the image analysis module, so that the image analysis module can be ensured to obtain the intraocular pressure measurement result of the human eye to be detected.
The invention provides a polarized imaging intraocular pressure detection method, which has the following technical scheme:
A method for detecting intraocular pressure by polarized imaging, the method comprising the steps of:
s1: obtaining the image information of the cornea region of the human eye to be detected by a polarization imaging method;
S2: establishing a deep learning network, and obtaining an intraocular pressure deep learning model capable of outputting intraocular pressure measurement results in a training mode;
s3: and (3) transmitting the image information of the cornea region of the detected human eye obtained in the step (S1) to the intraocular pressure deep learning model for analysis and calculation to obtain the intraocular pressure value of the detected human eye.
The invention provides a brand new intraocular pressure measurement method, which firstly adopts a polarization imaging method, and can acquire an intraocular pressure value by capturing cornea stress distribution state in real time. Secondly, the method adopts a deep learning channel to analyze the image of the cornea region, so that a more accurate intraocular pressure measurement result can be obtained. Compared with the existing applanation tonometer and pneumatic non-contact tonometer, the tonometer has higher measurement accuracy and wider applicable crowd including children, the elderly and other special crowds. Finally, the method is simple and convenient to operate, and diagnosis and treatment efficiency is improved.
Preferably, the step S1 includes the steps of:
S11: providing illumination light by a light source, and converting the illumination light provided by the light source into linearly polarized light with a extinction ratio not lower than 1000:1 by using a polarizing element;
s12: converting the linearly polarized light output by the polarizing element into circularly polarized light through a phase modulator and guiding the circularly polarized light to a cornea region of the human eye to be detected so as to be reflected by the cornea region of the human eye to be detected;
S13: converting the signal light reflected by the cornea region of the tested human eye into linearly polarized light through a conversion module;
S14: and acquiring image information of the cornea region of the tested human eye by using the imaging detection module through receiving the linearly polarized light output by the conversion module.
Preferably, the step S2 includes the steps of:
s21: establishing a deep learning network to be trained;
s22: obtaining a training data set comprising a cornea stress distribution state and corresponding intraocular pressure values;
S23: and training the deep learning network through the training data set by utilizing a data processing center to obtain the intraocular pressure deep learning model.
Preferably, the step S3 includes the steps of:
s31: performing image data preprocessing on the image information of the cornea region of the eye of the human eye to be detected, which is acquired in the step S14, wherein the image data preprocessing comprises image denoising and normalization operations;
S32: and inputting the processing result in the step S31 into the intraocular pressure deep learning model for analysis and calculation to obtain an intraocular pressure value.
Drawings
Fig. 1 is a schematic diagram of an optical path of a handheld polarized imaging intraocular pressure detection device according to the present invention;
Fig. 2 is a schematic structural diagram of a handheld polarized imaging intraocular pressure detecting device according to a first embodiment of the present invention;
fig. 3 is a flowchart of a polarized imaging intraocular pressure detection method according to a second embodiment of the present invention;
Fig. 4 is an image of the cornea region of a rabbit eye for training data set in accordance with a second embodiment of the present invention.
Wherein, the numbers marked in the figures represent respectively:
1. light source: 2. Polarizing element: 3. A phase modulator: 4. Circular lambda/4 plate: 5. circular linear polarizer: 6. an imaging lens; 7. a photodetector; 8. an image analysis module; 9. the human eye to be tested; 10. a conversion module; 11. and an imaging detection module.
Detailed Description
The technical solution of the present invention will be clearly and completely described below by using two embodiments in combination with the drawings in the corresponding embodiments.
Example 1
The embodiment provides a handheld polarization imaging intraocular pressure detection device, which comprises:
A light source 1 for generating illumination light;
A polarizing element 2 for converting illumination light into linearly polarized light having a extinction ratio of not less than 1000:1;
A phase modulator 3 for converting the linearly polarized light into circularly polarized light and guiding the circularly polarized light to the cornea region of the human eye 9 to be measured so as to be reflected by the cornea region of the human eye 9 to be measured;
the conversion module 10 is used for converting the signal light reflected by the cornea region of the tested human eye 9 into linearly polarized light;
the imaging detection module 11 is used for acquiring the cornea region image information of the detected human eye 9;
The image analysis module 8 is embedded with an intraocular pressure depth learning model and is used for collecting cornea region image information output by the imaging detection module 11 and calling the intraocular pressure depth learning model to obtain an intraocular pressure measurement result of the human eye 9 to be measured according to the cornea region image information output by the imaging detection module 11;
wherein,
The polarization element 2 and the phase modulator 3 are sequentially arranged along the propagation direction of illumination light, the conversion module 10 and the imaging detection module 11 are sequentially arranged along the propagation direction of signal light reflected by the cornea region of the tested human eye 9, and the image analysis module 8 is electrically connected with the imaging detection module 11.
For ease of understanding by those skilled in the art, the present embodiment provides for the determination of the angle and direction involved as follows:
first, choose to describe "clockwise" and "counterclockwise" for viewing angles facing the direction of beam propagation;
Setting the angle to be 0 DEG in the vertical direction and 0 DEG to 360 DEG in the clockwise direction;
Thirdly, regarding the placement angle of the linear polaroid, taking the polarization direction as the positive direction;
Fourth, for the angle of placement of the λ/4 plate, the fast axis direction is positive and the slow axis direction is negative.
In this embodiment, the light source 1 uses an LED annular light source, and the polarizing element 2 is an annular linear polarizer, which converts the light emitted by the light source 1 into linear polarized light with a high extinction ratio, where the extinction ratio can be up to 1000;1 and above, the linear polarizer is preferably set to 0 ° in the positive direction. Meanwhile, the phase modulator 3 is a circular λ/4 plate, which converts the linearly polarized light output from the polarizing element 2 into circularly polarized light. Preferably, the negative direction of the wave plate is set at 45 °.
In this embodiment, the conversion module 10 includes the following components in order along the propagation direction of the signal light reflected by the cornea region of the human eye 9:
The circular lambda/4 wave plate 4 is used for carrying out phase delay modulation on signal light reflected by the cornea region of the tested human eye 9;
A circular linear polarizer 5 for converting the light output from the circular lambda/4 wave plate 4 into linearly polarized light.
Further, the polarization direction of the circular λ/4 plate 4 is set opposite to that of the phase modulator 3, and further, its positive direction is set at 45 °. The polarization direction of the circular linear polarizer 5 is set orthogonal to the polarization direction of the polarizing element 2, and the positive direction thereof is set at 90 °.
In this embodiment, the imaging detection module 11 includes the following components in order along the propagation direction of the signal light reflected by the cornea region of the human eye 9:
the imaging lens 6 is used for imaging the cornea region of the human eye 9 to be tested to form an image of the cornea region of the human eye 9 to be tested;
The photoelectric detector 7 is used for receiving the cornea region image of the detected human eye 9 and converting the cornea region image into an electric signal of the cornea region image of the detected human eye 9;
wherein,
The photodetector 7 is electrically connected to the image analysis module 8.
The imaging lens 6 has the main function of clearly imaging a cornea image on the photodetector 7, and as an implementation mode, the photodetector of this embodiment adopts a color CMOS image detector.
As shown in fig. 2, as an implementation manner, the image analysis module 8 of this embodiment adopts a rasberry PI RASPBERRY group 4b 8gb motherboard, and embeds a trained intraocular pressure deep learning model, so that the image information acquired by the photodetector 7 can be subjected to deep learning analysis, and an intraocular pressure measurement result can be obtained.
Example two
Based on the first embodiment of the present invention, the present embodiment further provides a polarized imaging intraocular pressure detection method, including the following steps:
S1: obtaining the cornea region image information of the detected human eye 9 by a polarization imaging method;
In this embodiment, step S1 includes the following steps:
s11: providing illumination light by a light source 1, and converting the illumination light provided by the light source 1 into linearly polarized light with a extinction ratio of not less than 1000:1 by a polarizing element 2;
S12: the linearly polarized light output by the polarizing element 2 is converted into circularly polarized light by the phase modulator 3 and is directed to the cornea region of the human eye 9 to be measured so as to be reflected by the cornea region of the human eye 9 to be measured;
S13: the signal light reflected by the cornea region of the tested human eye 9 is converted into linearly polarized light through a conversion module 10;
s14: the imaging detection module 11 is used for acquiring the image information of the cornea region of the human eye 9 to be detected by receiving the linearly polarized light output by the conversion module 10.
S2: establishing a deep learning network, and obtaining an intraocular pressure deep learning model capable of outputting intraocular pressure measurement results in a training mode;
in this embodiment, step S2 includes the following steps:
s21: establishing a deep learning network to be trained, wherein a forward transmission network or a convolutional neural network can be selected;
s22: obtaining a training data set comprising a cornea stress distribution state and corresponding intraocular pressure values;
In view of the fact that the cornea structures of mammals such as rabbits are almost identical to those of humans, the embodiment uses the cornea of the rabbit as a sample when constructing the training set, and can record the corresponding intraocular pressure values by using a applanation tonometer after acquiring image information of a plurality of groups of cornea regions of the rabbit based on step S1. Then, the image information of a plurality of groups of cornea areas of the rabbit is taken as ideal input, and the corresponding intraocular pressure value is taken as ideal output, so that a training data set is formed.
S23: and training the deep learning network through a training data set by utilizing the data processing center to obtain an intraocular pressure deep learning model.
The deep learning model comprises an input layer, an intermediate layer and an output layer and a corresponding neural network structure; training the deep learning model by using a training data set, and optimizing model parameters by using a back propagation algorithm; and finally obtaining the intraocular pressure deep learning model.
After the intraocular pressure deep learning model is obtained, the intraocular pressure deep learning model can be subjected to model compression, which comprises the steps of model distillation, model pruning and model quantization, so as to obtain a miniaturized intraocular pressure deep learning model, and the miniaturized intraocular pressure deep learning model is deployed into the raspberry group 4B 8GB motherboard pointed out in the first embodiment, so as to obtain the image analysis module 8.
S3: and (3) transmitting the image information of the cornea region of the detected human eye 9 obtained in the step (S1) to an intraocular pressure deep learning model for analysis and calculation to obtain an intraocular pressure value of the detected human eye 9.
In this embodiment, step S3 includes the following steps:
S31: performing image data preprocessing on the image information of the cornea region of the detected human eye 9 obtained in the step S14, wherein the image data preprocessing comprises image denoising and normalization operations;
S32: and (3) inputting the processing result in the step (S31) into an intraocular pressure deep learning model for analysis and calculation to obtain an intraocular pressure value.
Although a particular embodiment of the present invention has been shown and described with two embodiments, it will be apparent to those skilled in the art that various changes, modifications, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims and their equivalents.
Claims (8)
1. A hand-held polarization imaging intraocular pressure detection device is characterized in that: comprising the following steps:
A light source (1) for generating illumination light;
a polarizing element (2) for converting the illumination light into linearly polarized light having a extinction ratio of not less than 1000:1;
a phase modulator (3) for converting the linearly polarized light into circularly polarized light and directing it to the cornea region of the human eye (9) to be measured so as to be reflected by the cornea region of the human eye (9) to be measured;
the conversion module (10) is used for converting signal light reflected by the cornea region of the tested human eye (9) into linearly polarized light;
The imaging detection module (11) is used for acquiring the cornea region image information of the detected human eye (9);
The image analysis module (8) is embedded with an intraocular pressure deep learning model and is used for collecting cornea region image information output by the imaging detection module (11) and calling the intraocular pressure deep learning model to obtain an intraocular pressure measurement result of the detected human eye (9) according to the cornea region image information output by the imaging detection module (11);
wherein,
The polarization element (2) and the phase modulator (3) are sequentially arranged along the propagation direction of the illumination light, the conversion module (10) and the imaging detection module (11) are sequentially arranged along the propagation direction of the signal light reflected by the cornea region of the tested human eye (9), and the image analysis module (8) is electrically connected with the imaging detection module (11);
the conversion module (10) comprises the following components in sequence along the propagation direction of the signal light reflected by the cornea region of the human eye (9) to be tested:
The circular lambda/4 wave plate (4) is used for carrying out phase delay modulation on the signal light reflected by the cornea region of the tested human eye (9);
a circular linear polarizer (5) for converting the light outputted from the circular lambda/4 wave plate (4) into linearly polarized light;
The polarization direction of the circular lambda/4 wave plate (4) is opposite to the polarization direction of the phase modulator (3), and the polarization direction of the circular linear polaroid (5) is orthogonal to the polarization direction of the polarization element (2).
2. The hand-held polarized imaging intraocular pressure detection device of claim 1 wherein: the polarizing element (2) is an annular linear polarizer.
3. The hand-held polarized imaging intraocular pressure detection device of claim 2 wherein: the phase modulator (3) is a ring lambda/4 wave plate.
4. The hand-held polarized imaging intraocular pressure detection device of claim 1 wherein: the imaging detection module (11) comprises the following components in sequence along the propagation direction of signal light reflected by the cornea region of the human eye (9) to be detected:
the imaging lens (6) is used for imaging the cornea region of the detected human eye (9) to form a cornea region image of the detected human eye (9);
The photoelectric detector (7) is used for receiving the cornea region image of the human eye (9) to be detected and converting the cornea region image of the human eye (9) to be detected into an electric signal;
wherein,
The photodetector (7) is electrically connected with the image analysis module (8).
5. A polarized imaging intraocular pressure detection method is characterized in that: a hand-held polarized imaging intraocular pressure detection device for use in any one of claims 1 to 4, comprising the steps of:
s1: obtaining cornea region image information of a tested human eye (9) by a polarization imaging method;
S2: establishing a deep learning network, and obtaining an intraocular pressure deep learning model capable of outputting intraocular pressure measurement results in a training mode;
s3: and (3) transmitting the cornea region image information of the tested human eye (9) obtained in the step (S1) to the intraocular pressure deep learning model for analysis and calculation to obtain an intraocular pressure value of the tested human eye (9).
6. The polarized imaging intraocular pressure detection method according to claim 5, wherein: the step S1 includes the steps of:
S11: providing illumination light through a light source (1), and converting the illumination light provided by the light source (1) into linearly polarized light with a extinction ratio of not less than 1000:1 by using a polarizing element (2);
S12: converting the linearly polarized light output by the polarizing element (2) into circularly polarized light through a phase modulator (3) and guiding the circularly polarized light to a cornea region of the human eye (9) to be tested so as to be reflected by the cornea region of the human eye (9) to be tested;
s13: converting signal light reflected by a cornea region of the tested human eye (9) into linearly polarized light through a conversion module (10);
s14: and acquiring the image information of the cornea region of the eye (9) of the tested person by using an imaging detection module (11) through receiving the linearly polarized light output by the conversion module (10).
7. The polarized imaging intraocular pressure detection method according to claim 6, wherein: the step S2 includes the steps of:
s21: establishing a deep learning network to be trained;
s22: obtaining a training data set comprising a cornea stress distribution state and corresponding intraocular pressure values;
S23: and training the deep learning network through the training data set by utilizing a data processing center to obtain the intraocular pressure deep learning model.
8. The polarized imaging intraocular pressure detection method according to claim 7, wherein: the step S3 includes the steps of:
S31: performing image data preprocessing on the image information of the cornea region of the detected human eye (9) acquired by the step S14, wherein the image data preprocessing comprises image denoising and normalization operations;
S32: and inputting the processing result in the step S31 into the intraocular pressure deep learning model for analysis and calculation to obtain an intraocular pressure value.
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