Visual impairment prediction method and system based on noninvasive measurement of gas pressure of excessive gasification sphenoid sinus cavity

Abstract

The invention belongs to but is not limited to the technical field of visual impairment prediction, and discloses a gas pressure noninvasive measurement and visual impairment prediction method based on sphenoid sinus volume and bone mineral density, which comprises the following steps of: scanning by using high-resolution CT (Computed Tomography) to obtain a three-dimensional image of sphenoid sinus, and calculating the volume of the sphenoid sinus by using an image processing module; the thickness and strength of the sphenoid sinus wall are estimated through bone mineral density measurement of the CT image; based on the sphenoid sinus volume and bone mineral density data, calculating gas pressure in the sphenoid sinus by using a gas pressure calculation module, and correcting the influence of the gas pressure in combination with the bone mineral density; and the risk assessment module automatically assesses the visual impairment risk by using a prediction statistical model in combination with gas pressure and historical data of optic nerve damage, and gives corresponding diagnosis suggestions. According to the method, the visual impairment accompanied by excessive sphenoid sinus gasification can be predicted in an early stage, clinicians are helped to intervene in time, and the risk of visual impairment is reduced.

Description

Technical Field

[0001] The present invention belongs to but is not limited to the technical field of vision impairment prediction, and in particular relates to a method and system for non-invasive measurement of gas pressure and prediction of vision impairment based on sphenoid sinus volume and bone density. Background Art

[0002] Excessive pneumatization of the sphenoid sinus is a common phenomenon in imaging examinations, which is mainly manifested as an abnormal increase in the volume of the sphenoid sinus air cavity. Although the specific reasons for its impact on health are still unclear, there are literature hypotheses that excessive gas pressure in the sphenoid sinus may cause morphological changes in the optic canal, thereby leading to optic nerve damage and visual impairment. However, because the sphenoid sinus is deeply hidden in the intracranial structure, it is difficult to directly measure the gas pressure inside the sphenoid sinus. Existing clinical methods mostly rely on imaging evaluation, and it is impossible to measure the gas pressure in the sphenoid sinus non-invasively and in real time. The lack of this measurement method limits the medical community's in-depth understanding and real-time monitoring of the impact of excessive pneumatization of the sphenoid sinus on the optic nerve, and a method for measuring the sphenoid sinus air cavity pressure is urgently needed.

[0003] In response to this demand, it is urgent to develop an innovative non-invasive measurement technology to accurately monitor the gas pressure in the sphenoid sinus to reveal the relationship between excessive gasification of the sphenoid sinus and optic nerve damage. The ideal measurement method needs to have the following characteristics: 1) reduce trauma and discomfort to patients, 2) real-time monitoring, and the ability to dynamically track the changing trend of sphenoid sinus pressure, and 3) high sensitivity and high accuracy to ensure the reliability of measurement data.

[0004] At present, some studies are exploring the possibility of non-invasive measurement methods. For example, combining sound wave measurement with sensor technology, the reflection and refraction characteristics of sound waves in the sinus cavity are used to calculate the gas pressure in the sinus cavity; or, using low-intensity ultrasonic equipment, the air cavity pressure value is estimated through the relationship between sound wave reflection and sinus cavity gas density and pressure. In addition, infrared thermal imaging technology attempts to measure changes in sinus cavity gas temperature, and combines the ideal gas law (PV=nRT) to convert the trend of pressure changes in the air cavity. The further development of these technologies will provide new solutions for the non-invasive measurement of sphenoid sinus vaporization pressure, provide accurate data support for related medical research, and is expected to eventually reveal the association mechanism between excessive sphenoid sinus vaporization and optic nerve damage. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a method and system for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density.

[0006] This method uses non-invasive CT imaging combined with innovative data processing methods to measure the gas pressure in the sphenoid sinus. At present, there is no mature non-invasive technology for direct measurement of gas pressure in the sphenoid sinus. Most of the existing literature uses imaging methods to indirectly evaluate the pressure situation through changes in the volume of the sphenoid sinus, or obtains data through invasive methods, all of which have limitations. Imaging methods can only provide static images and it is difficult to accurately reflect the dynamic fluctuations of gas pressure in the sphenoid sinus; and invasive methods are not suitable for routine clinical testing. Therefore, the pressure estimation method based on CT images proposed in the present invention fills the gap in the prior art and provides a non-invasive method for monitoring sphenoid sinus pressure.

[0007] At present, some studies have tried to use sound wave reflection, ultrasound, infrared temperature measurement and other methods to indirectly evaluate sphenoid sinus pressure, but these methods have low sensitivity and accuracy. For example, due to the deep location and complex structure of the sphenoid sinus, the signal transmission of sound waves and ultrasound is easily disturbed, resulting in poor measurement accuracy; infrared thermal imaging is limited by the inference of pressure due to temperature fluctuations, and its accuracy is limited. In contrast, this method can provide real-time and dynamic sphenoid sinus pressure monitoring without intervention by combining CT images with **[specific analysis algorithms or models, such as gas pressure estimation models or sphenoid sinus geometric parameter analysis technology]**. This method not only improves the sensitivity and accuracy of the data, but also avoids the risk of invasive operations. It is suitable for clinical monitoring of the potential impact of excessive gasification of the sphenoid sinus on the health of the optic nerve.

[0008] Therefore, this method significantly improves the feasibility and safety of gas pressure monitoring in the sphenoid sinus under non-invasive detection. Its innovation is that it can directly calculate the gas pressure in the sphenoid sinus through the combination of CT images and data analysis models, providing reliable technical support for revealing the relationship between sphenoid sinus gasification and optic nerve damage.

[0009] The present invention is implemented as follows: a method for non-invasively measuring gas pressure and predicting visual impairment based on sphenoid sinus volume and bone density, comprising the following steps:

[0010] Step 1: Use high-resolution computed tomography (CT) scanning to obtain a three-dimensional image of the sphenoid sinus, and use an image processing module to calculate the volume of the sphenoid sinus;

[0011] Step 2, the thickness and strength of the sphenoid sinus wall were estimated by the CT value (Hounsfield, HU) of the CT images;

[0012] Step 3: Based on the sphenoid sinus volume and bone density data, the gas pressure in the sphenoid sinus is calculated using the gas pressure calculation module, and the effect of the gas pressure is corrected in combination with the bone density;

[0013] Step 4: The risk assessment module uses a predictive statistical model to combine gas pressure with the degree of optic nerve damage in clinical patients to assess and predict the risk of visual impairment and assist in clinical diagnosis.

[0014] Furthermore, in step 1, the volume calculation method is as follows: based on the size and density of each voxel in the CT image, an automatic or semi-automatic segmentation algorithm is used to determine the boundary of the sphenoid sinus and calculate its volume; the algorithm includes edge detection, region growing and other techniques for automatically identifying the boundary of the sphenoid sinus.

[0015] Furthermore, in step 3, the gas pressure calculation module calculates the gas pressure in the sphenoid sinus using the ideal gas state equation, with the basic assumption that the gas in the sphenoid sinus complies with the ideal gas law, that is, PV = nRT, where:

[0016] P is the gas pressure in the sphenoid sinus;

[0017] V is the volume of the sphenoid sinus;

[0018] n is the number of moles of gas;

[0019] R is the gas constant;

[0020] T is the gas temperature (normal human body temperature is about 37°C)

[0021] By calculating the volume V of the sphenoid sinus, the pressure changes in the sphenoid sinus can be indirectly inferred.

[0022] Furthermore, the method for constructing the prediction statistical model includes:

[0023] Data collection: A large amount of clinical data on sphenoid sinus volume, bone density, and optic nerve damage were collected from different patients for model training;

[0024] Machine learning model: Use machine learning algorithms, such as linear regression or random forest, to predictively model the relationship between sphenoid sinus volume, bone density, and gas pressure and visual impairment, and obtain a predictive statistical model for automatically identifying the risk of optic nerve damage.

[0025] Furthermore, the correlation analysis method between gas pressure and optic nerve damage includes:

[0026] Based on data samples from different populations, determine the range of intrasphenoidal gas pressure in normal people, patients with sphenoidal hyperpneumatization but no optic nerve damage, and patients with sphenoidal hyperpneumatization accompanied by visual impairment;

[0027] Based on the predictive statistical model, combined with the pressure and the patient's optic nerve damage, the critical value of the gas pressure in the sphenoid sinus was derived as the risk threshold for predicting optic nerve damage.

[0028] Another object of the present invention is to provide a method for non-invasive measurement of gas pressure based on sphenoid sinus volume and bone density and prediction of visual impairment, comprising:

[0029] Data acquisition module for sphenoid sinus 3D imaging and bone density measurement;

[0030] An image processing module, used to automatically identify the boundary of the sphenoid sinus in the three-dimensional image of the sphenoid sinus and calculate the volume of the sphenoid sinus;

[0031] The gas pressure calculation module uses the ideal gas state equation to calculate the gas pressure in the sphenoid sinus based on the sphenoid sinus volume and bone density data, and corrects the effect of gas pressure in combination with bone density;

[0032] The risk assessment module uses a predictive statistical model, combined with historical data on gas pressure and optic nerve damage, to automatically assess the patient's risk of visual impairment and provide corresponding diagnostic recommendations;

[0033] The user interface provides an easy-to-operate interface, including a patient data input interface, a CT image display interface, a gas pressure calculation result, and a visual impairment prediction interface.

[0034] Another object of the present invention is to provide a non-invasive gas pressure measurement and vision impairment prediction method based on sphenoid sinus volume and bone density, and a device for non-invasive gas pressure measurement and vision impairment prediction based on sphenoid sinus volume and bone density, comprising:

[0035] CT imaging equipment: high-resolution CT scanner for 3D imaging of the sphenoid sinus and measurement of bone density.

[0036] Processor and memory: used to process large amounts of CT image data and calculate sphenoid sinus volume and gas pressure;

[0037] Visualization and interactive equipment: doctor workstation (high-performance computer, display, etc.) for result presentation and diagnostic assistance.

[0038] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density.

[0039] Another object of the present invention is to provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density.

[0040] Another object of the present invention is to provide an information data processing terminal, which includes the non-invasive gas pressure measurement and vision impairment prediction system based on sphenoid sinus volume and bone density.

[0041] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0042] First, the present invention uses mathematical modeling and non-invasive measurement methods to indirectly measure the gas pressure in the sphenoid sinus using parameters such as the sphenoid sinus volume and bone density in CT images. Combined with statistical and machine learning models, it can make early predictions of visual impairment associated with excessive gasification of the sphenoid sinus, helping clinicians to intervene in time and reduce the risk of visual impairment. It is of great significance for early prediction of visual impairment and diagnosis and intervention of patients with excessive gasification.

[0043] Second, the non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density proposed in the present invention has significantly solved the current problem of detecting the potential damage of sphenoid sinus pneumatization to the optic nerve in industrial applications, and has brought about the following important technical advances:

[0044] 1. Non-invasive measurement of sphenoid sinus pressure

[0045] Existing sphenoid sinus pressure detection lacks non-invasive means and cannot directly monitor the gas pressure in the sphenoid sinus, which limits the research on the relationship between excessive gasification of the sphenoid sinus and visual impairment. The present invention uses high-resolution CT imaging combined with bone density data to estimate the internal gas pressure through the sphenoid sinus volume and bone density to achieve the effect of non-invasive measurement, overcome the limitations of traditional methods, and meet the clinical demand for non-invasive detection of sphenoid sinus pressure.

[0046] 2. Accurately quantify the effect of sphenoid sinus pressure on the optic nerve

[0047] This method calculates the volume of the sphenoid sinus and bone density, uses a physical model to accurately estimate the air cavity pressure, and combines a large amount of optic nerve damage case data for statistical analysis to quantify the potential impact of pressure on the optic nerve. This precise quantification method provides clinicians with quantitative indicators and objective references, significantly improving the accuracy of diagnosis. 3. Automated visual impairment risk assessment

[0048] The present invention compares the calculated sphenoid sinus pressure data with the historical data of optic nerve damage, and uses the risk assessment model to automatically assess visual impairment and generate diagnostic recommendations. This automated risk prediction model reduces the judgment burden on doctors, improves diagnostic efficiency and reliability, and achieves significant technical progress in terms of efficiency and intelligence.

[0049] 4. Reduce the difficulty of early prediction of visual impairment

[0050] Traditional detection methods make it difficult to detect abnormal sphenoid sinus pressure in the early stages of visual impairment. The present invention analyzes changes in sphenoid sinus pressure through CT images, can identify high-risk cases early, conduct preventive interventions, and reduce the long-term hidden dangers of visual impairment, thus having high industrial application value.

[0051] 5. Wider clinical applicability

[0052] Since the detection method of the present invention is non-invasive, accurate, and can be applied to the routine operation of CT equipment, it is suitable for wide application in the fields of ophthalmology, otolaryngology, neurology, etc. Especially for patients with visual impairment caused by sphenoid sinus pneumatization, the changes in sphenoid sinus pressure can be obtained during physical examination, providing early warning for further diagnosis and treatment, and the applicability is greatly enhanced.

[0053] This invention has achieved significant technological advancement over existing technologies in terms of non-invasive detection accuracy, automated diagnosis and prediction of visual impairment risk. It has brought unprecedented convenience and accuracy to the clinical detection of sphenoid sinus pneumatization risk and has great prospects for industrial application. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of a method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density provided by an embodiment of the present invention;

[0055] Figure 2 It is a structural diagram of a system for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0057] like Figure 1 As shown, the embodiment of the present invention provides a method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density, comprising the following steps:

[0058] Step 1: Use high-resolution computed tomography (CT) scanning to obtain a three-dimensional image of the sphenoid sinus, and use an image processing module to calculate the volume of the sphenoid sinus;

[0059] Step 2, estimate the thickness and strength of the sphenoid sinus wall by bone density measurement (Hounsfield units) on CT images;

[0060] Step 3: Based on the sphenoid sinus volume and bone density data, the gas pressure in the sphenoid sinus is calculated using the gas pressure calculation module, and the effect of the gas pressure is corrected in combination with the bone density;

[0061] Step 4: The risk assessment module uses a predictive statistical model, combined with historical data on gas pressure and optic nerve damage, to automatically assess the risk of vision impairment and provide corresponding diagnostic recommendations.

[0062] The present invention proposes a non-invasive gas pressure measurement and vision impairment prediction method based on sphenoid sinus volume and bone density. This method accurately estimates the gas pressure in the sphenoid sinus through multi-step image and data analysis, further assesses the risk of optic nerve damage, and provides a reliable diagnostic basis for clinicians. Its main principles can be divided into the following aspects:

[0063] Step 1: Non-invasive acquisition of sphenoid sinus volume

[0064] This method first uses high-resolution CT scanning to obtain the anatomical structure of the sphenoid sinus in the form of a three-dimensional image. Through the image processing module, image segmentation and reconstruction technology are used to extract the volume information of the sphenoid sinus area. The volume of the sphenoid sinus directly affects the gas pressure inside it. Especially in the case of excessive gasification, the abnormal increase in the volume of the air cavity may lead to changes in local gas pressure, which becomes a major factor affecting the optic nerve. Through accurate sphenoid sinus volume measurement, a data basis is provided for subsequent gas pressure estimation.

[0065] Step 2: Measurement of sphenoid sinus wall bone density

[0066] Using the Hounsfield unit (HU value) data of CT images, the system can measure the bone density of the sphenoid sinus wall. Bone density is an important indicator for predicting the thickness and strength of the sphenoid sinus wall. The thicker the sphenoid sinus wall and the higher the bone density, the stronger the resistance to changes in pressure in the air cavity. Bone density measurement through CT images can not only evaluate the thickness of the sphenoid sinus wall, but also indirectly reflect the tolerance to gas pressure in the sphenoid sinus, providing a more accurate model basis for evaluating the potential damage caused by air cavity pressure.

[0067] Step 3: Estimation of gas pressure in the sphenoid sinus

[0068] After obtaining the sphenoid sinus volume and bone density data, the gas pressure calculation module calculates the gas pressure in the sphenoid sinus using a physical formula. Considering that the gas pressure is inversely proportional to the volume, the system estimates the pressure based on the actual measured volume. In addition, the bone density of the sphenoid sinus wall will affect the pressure tolerance of the air cavity, so this module uses bone density data to correct the pressure model to ensure that the estimated gas pressure is closer to the actual pressure level of the sphenoid sinus. This non-invasive pressure measurement technology provides key data for speculating the potential impact of sphenoid sinus pressure on the optic nerve.

[0069] Step 4: Prediction of risk of visual impairment

[0070] Based on the estimated gas pressure in the sphenoid sinus, the system compares it with the optic nerve damage data of previous patients. Through statistical models, the risk assessment module can identify the degree of correlation between air cavity pressure and optic nerve damage. The model considers the damage to the optic nerve under different pressures, and combines the bone density of the sphenoid sinus wall to establish a dynamic relationship between pressure and visual impairment. If the currently measured sphenoid sinus pressure exceeds the safety threshold, the system will automatically indicate a high risk of visual impairment, helping doctors make decisions on early intervention.

[0071] Step 5: Automated diagnostic suggestion generation

[0072] The risk assessment module generates specific diagnostic recommendations for clinicians based on the calculation results. This diagnostic recommendation is based on a large amount of data and statistical models, and can automatically analyze the potential impact of sphenoid sinus volume, bone density and gas pressure on the optic nerve. When the patient's sphenoid sinus air pressure is at a high risk, the system will recommend further examination or intervention. This automated diagnostic process significantly reduces the doctor's judgment burden and improves the objectivity of the diagnosis.

[0073] Step 6: Application scenarios and dynamic monitoring

[0074] This method can be widely used in patients who need to detect sphenoid sinus pressure, such as patients with orbital compression or suspected optic nerve damage, to provide dynamic, non-invasive pressure monitoring. Combined with the sphenoid sinus pressure trend measured multiple times, the system can dynamically analyze the changes in air cavity pressure and track and warn the risk of optic nerve damage. This real-time monitoring capability is particularly important in clinical practice, as it can detect potential risks in a timely manner and avoid visual impairment caused by excessive pneumatization of the sphenoid sinus.

[0075] The invented non-invasive measurement method provides scientific support for gas pressure estimation and vision impairment prediction through combined analysis of sphenoid sinus volume and bone density data, which helps to efficiently carry out research and early prevention of optic nerve damage caused by sphenoid sinus pneumatization.

[0076] Volume calculation method in step 1: Based on the size and density of each voxel in the CT image, an automatic or semi-automatic segmentation algorithm is used to determine the boundary of the sphenoid sinus and calculate its volume; the algorithm includes edge detection, region growing and other technologies for automatically identifying the boundary of the sphenoid sinus.

[0077] In step 2, bone density is a factor that affects the ability of the sphenoid sinus wall to withstand the internal and external pressure difference; a relationship model between bone density and sphenoid sinus pressure changes is used to infer whether there is pressure-induced sphenoid sinus dilatation or optic canal deformation.

[0078] In step 3, the gas pressure calculation module calculates the gas pressure in the sphenoid sinus using the ideal gas state equation, with the basic assumption that the gas in the sphenoid sinus conforms to the ideal gas law, that is, PV = nRT, where:

[0079] P is the gas pressure in the sphenoid sinus;

[0080] V is the volume of the sphenoid sinus;

[0081] n is the number of moles of gas;

[0082] R is the gas constant;

[0083] T is the gas temperature (normal human body temperature is about 37°C)

[0084] By calculating the volume V of the sphenoid sinus, the pressure changes in the sphenoid sinus can be indirectly inferred.

[0085] The method for constructing the prediction statistical model in step 4 includes:

[0086] Data collection: A large amount of clinical data on sphenoid sinus volume, bone density, and optic nerve damage were collected from different patients for model training;

[0087] Machine learning model: Use machine learning algorithms, such as linear regression or random forest, to predictively model the relationship between sphenoid sinus volume, bone density, and gas pressure and visual impairment, and obtain a predictive statistical model for automatically identifying the risk of optic nerve damage.

[0088] Furthermore, the correlation analysis method between gas pressure and optic nerve damage includes:

[0089] Based on data samples from different populations, determine the range of intrasphenoidal gas pressure in normal people, patients with sphenoidal hyperpneumatization but no optic nerve damage, and patients with sphenoidal hyperpneumatization accompanied by visual impairment;

[0090] Based on the predictive statistical model, combined with the pressure and the patient's optic nerve damage, the critical value of the gas pressure in the sphenoid sinus was derived as the risk threshold for predicting optic nerve damage.

[0091] like Figure 2 As shown, the embodiment of the present invention provides a method for non-invasive measurement of gas pressure based on sphenoid sinus volume and bone density and prediction of visual impairment, comprising:

[0092] Data acquisition module for sphenoid sinus 3D imaging and bone density measurement;

[0093] An image processing module, used to automatically identify the boundary of the sphenoid sinus in the three-dimensional image of the sphenoid sinus and calculate the volume of the sphenoid sinus;

[0094] The gas pressure calculation module uses the ideal gas state equation to calculate the gas pressure in the sphenoid sinus based on the sphenoid sinus volume and bone density data, and corrects the effect of gas pressure in combination with bone density;

[0095] The risk assessment module uses a predictive statistical model, combined with historical data on gas pressure and optic nerve damage, to automatically assess the patient's risk of visual impairment and provide corresponding diagnostic recommendations;

[0096] The user interface provides an easy-to-operate interface, including a patient data input interface, a CT image display interface, a gas pressure calculation result, and a visual impairment prediction interface.

[0097] The embodiment of the present invention provides a non-invasive gas pressure measurement method based on sphenoid sinus volume and bone density and a device for predicting visual impairment based on sphenoid sinus volume and bone density, comprising:

[0098] CT imaging equipment: high-resolution CT scanner for 3D imaging of the sphenoid sinus and measurement of bone density.

[0099] Processor and memory: used to process large amounts of CT image data and calculate sphenoid sinus volume and gas pressure;

[0100] Visualization and interactive equipment: doctor workstation (high-performance computer, display, etc.) for result presentation and diagnostic assistance.

[0101] Example 1

[0102] 1. Patient examination: The patient undergoes a CT scan to obtain a three-dimensional image of the sphenoid sinus.

[0103] 2. Data processing: The system automatically analyzes the images and extracts the sphenoid sinus volume and bone density.

[0104] 3. Gas pressure calculation: Based on the mathematical model, the gas pressure in the sphenoid sinus is calculated.

[0105] 4. Risk prediction: Input pressure data into the prediction model to assess the risk of vision impairment.

[0106] 5. Diagnosis and intervention: Based on the predicted results, doctors can choose to intervene early to reduce the risk of visual impairment.

[0107] The specific application fields or related products of the present invention.

[0108] 1. Early warning system: Through non-invasive measurement of sphenoid sinus gas pressure in patients with excessive gasification, the risk of optic nerve damage is predicted, alerting doctors to perform early intervention.

[0109] 2. Real-time diagnosis: Combining the real-time CT scanning of hardware equipment and the automatic analysis of software ensures that the diagnosis process is fast and efficient.

[0110] 3. Optimize algorithms and model accuracy: Through the accumulation of more clinical data, continuously optimize algorithms and mathematical models to improve the accuracy of gas pressure measurement and risk prediction.

[0111] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0112] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density, characterized in that: The following steps are involved: Step 1: Use high-resolution CT scanning to obtain a three-dimensional image of the sphenoid sinus, and use an image processing module to calculate the volume of the sphenoid sinus; Step 2, estimate the thickness and strength of the sphenoid sinus wall by bone density measurement on CT images; Step 3: Based on the sphenoid sinus volume and bone density data, the gas pressure in the sphenoid sinus is calculated using the gas pressure calculation module, and the effect of the gas pressure is corrected in combination with the bone density; Step 4: The risk assessment module uses a predictive statistical model, combined with historical data on gas pressure and optic nerve damage, to automatically assess the risk of vision impairment and provide corresponding diagnostic recommendations.

2. The method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density as claimed in claim 1, characterized in that: The volume calculation method in step 1 is as follows: based on the size and density of each voxel in the CT image, an automatic or semi-automatic segmentation algorithm is used to determine the boundary of the sphenoid sinus and calculate its volume; the algorithm includes edge detection and region growing technology for automatically identifying the boundary of the sphenoid sinus.

3. The method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density as claimed in claim 1, characterized in that: In step 3, the gas pressure calculation module calculates the gas pressure in the sphenoid sinus using the ideal gas state equation, with the basic assumption that the gas in the sphenoid sinus conforms to the ideal gas law, that is, PV = nRT, where: P is the gas pressure in the sphenoid sinus; V is the volume of the sphenoid sinus; n is the number of moles of gas; R is the gas constant; T is the gas temperature.

4. The method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density as claimed in claim 1, characterized in that: The method for constructing the prediction statistical model comprises: Data collection: A large amount of clinical data on sphenoid sinus volume, bone density, and optic nerve damage were collected from different patients for model training; Machine learning model: Use machine learning algorithms, such as linear regression or random forest, to predictively model the relationship between sphenoid sinus volume, bone density, and gas pressure and visual impairment, and obtain a predictive statistical model for automatically identifying the risk of optic nerve damage.

5. The method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density as claimed in claim 4, characterized in that: The correlation analysis method between gas pressure and optic nerve damage includes: Based on data samples from different populations, determine the range of intrasphenoidal gas pressure in normal people, patients with sphenoidal hyperpneumatization but no optic nerve damage, and patients with sphenoidal hyperpneumatization accompanied by visual impairment; Based on the predictive statistical model, combined with the pressure and the patient's optic nerve damage, the critical value of the gas pressure in the sphenoid sinus was derived as the risk threshold for predicting optic nerve damage.

6. A method system for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density according to any one of claims 1 to 5, characterized in that: include: Data acquisition module for sphenoid sinus 3D imaging and bone density measurement; An image processing module, used to automatically identify the boundary of the sphenoid sinus in the three-dimensional image of the sphenoid sinus and calculate the volume of the sphenoid sinus; The gas pressure calculation module uses the ideal gas state equation to calculate the gas pressure in the sphenoid sinus based on the sphenoid sinus volume and bone density data, and corrects the effect of gas pressure in combination with bone density; The risk assessment module uses a predictive statistical model, combined with historical data on gas pressure and optic nerve damage, to automatically assess the patient's risk of visual impairment and provide corresponding diagnostic recommendations; The user interface provides an easy-to-operate interface, including a patient data input interface, a CT image display interface, a gas pressure calculation result, and a visual impairment prediction interface.

7. A device for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density according to any one of claims 1 to 5, characterized in that: include: CT imaging equipment: high-resolution CT scanner for 3D imaging of the sphenoid sinus and measurement of bone density. Processor and memory: used to process large amounts of CT image data and calculate sphenoid sinus volume and gas pressure; Visualization and interactive equipment: doctor workstation (high-performance computer, display, etc.) for result presentation and diagnostic assistance.

8. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density as described in any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to execute the steps of the method for non-invasive measurement of gas pressure and prediction of visual impairment based on sphenoid sinus volume and bone density as described in any one of claims 1 to 5.

10. An information data processing terminal, characterized in that: The information data processing terminal includes the non-invasive gas pressure measurement and vision impairment prediction system based on sphenoid sinus volume and bone density as described in claim 6.

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