A method and apparatus for measuring ventilation based on dr

Abstract

The application discloses a DR-based ventilation measurement method and device, which comprises the following steps: obtaining body information of a user to be measured; matching the body information of the user to be measured with a pre-obtained incident energy reference benchmark set to obtain a corresponding incident energy reference benchmark; and exposing the body to be measured to the incident energy reference benchmark to obtain a ventilation image. The method can select a proper incident energy reference benchmark for exposure according to different bodies to be measured, so that a more accurate ventilation image is obtained. Therefore, the corresponding gas thickness and gas area at each moment are obtained based on the ventilation image and the incident energy reference benchmark, and accurate ventilation data is obtained. Meanwhile, the ventilation image is obtained based on digital X-ray photography, so that the ventilation can be measured while the X-ray image is taken.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ventilation measurement, in particular to a DR-based ventilation measurement method and device. BACKGROUND

[0002] A conventional ventilation measurement method is to use a dedicated spirometer to measure. When using the spirometer, the user needs to blow air into the spirometer device. The spirometer measures the air flow rate according to the relationship between the air flow blown by the user and the set detectable variable in the device, and obtains the ventilation by integrating in time. However, the measurement accuracy of the spirometer is low, and when the user does not operate normally, the accuracy of the measurement result will be further affected. SUMMARY

[0003] The present application solves the technical problem of providing a DR-based ventilation measurement method and device, which can measure the lung ventilation while taking X-ray images.

[0004] In order to solve the above technical problems, the technical scheme adopted by the present application is:

[0005] A DR-based ventilation measurement method, comprising the steps of:

[0006] obtaining a set of calibrated incident energy reference bases;

[0007] obtaining the body information of a user to be measured, and matching the body information of the user to be measured with the set of incident energy reference bases to obtain an incident energy reference base corresponding to the body information of the user to be measured;

[0008] obtaining a ventilation image corresponding to each time point in a preset time period according to the incident energy reference base;

[0009] obtaining a gas thickness corresponding to each time point according to the incident energy reference base and the ventilation image, and obtaining a gas area corresponding to each time point according to the ventilation image;

[0010] obtaining the ventilation according to the gas area and the gas thickness corresponding to each time point.

[0011] In order to solve the above technical problems, another technical scheme adopted by the present application is:

[0012] A ventilation measurement device, comprising:

[0013] a calibration module for obtaining a set of calibrated incident energy reference bases;

[0014] The acquisition control module is configured to acquire body information of a user to be measured, match the body information of the user to be measured with the set of incident energy reference benchmarks, obtain an incident energy reference benchmark corresponding to the body information of the user to be measured, and obtain a ventilation volume image corresponding to each time point in a preset time period according to the incident energy reference benchmark.

[0015] The image processing module is configured to obtain a gas thickness corresponding to each time point according to the incident energy reference benchmark and the ventilation volume image, and obtain a gas area corresponding to each time point according to the ventilation volume image, and obtain a ventilation volume according to the gas area and the gas thickness corresponding to each time point.

[0016] The present application has the advantages that: after acquiring the body information of the user to be measured, the body information of the user to be measured is matched with the set of incident energy reference benchmarks obtained in advance to obtain a corresponding incident energy reference benchmark, and then the user to be measured is exposed to the incident energy reference benchmark to obtain a ventilation volume image, that is, a suitable incident energy reference benchmark can be selected according to different users to be measured to obtain a more accurate ventilation volume image, so that the gas thickness and the gas area corresponding to each time point are obtained based on the ventilation volume image and the incident energy reference benchmark, and then accurate ventilation volume data are obtained; at the same time, the ventilation volume image is obtained based on digital X-ray photography, that is, the ventilation volume can be measured while the X-ray image is taken. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 A step flow chart of a DR-based ventilation volume measurement method in an embodiment of the present application;

[0018] Figure 2 A comparison chart of exposure image processing in a DR-based ventilation volume measurement method in an embodiment of the present application;

[0019] Figure 3 A gas volume change curve obtained based on a DR-based ventilation volume measurement method in an embodiment of the present application;

[0020] Figure 4 A gas flow rate change curve obtained based on a DR-based ventilation volume measurement method in an embodiment of the present application;

[0021] Figure 5 A structural schematic diagram of a ventilation volume measurement device in an embodiment of the present application. DETAILED DESCRIPTION

[0022] To make the technical content, purposes and effects of the present application clear, the following will be described in detail in combination with embodiments and the accompanying drawings.

[0023] Please refer to Figure 1A DR-based ventilation measurement method comprises the steps of:

[0024] Obtaining a set of calibrated incident energy reference bases;

[0025] Obtaining body information of a user to be measured, and matching the body information of the user to be measured with the set of incident energy reference bases to obtain an incident energy reference base corresponding to the body information of the user to be measured;

[0026] Obtaining a ventilation image corresponding to each time in a preset time period according to the incident energy reference base;

[0027] Obtaining a gas thickness corresponding to each time according to the incident energy reference base and the ventilation image, and obtaining a gas area corresponding to each time according to the ventilation image;

[0028] Obtaining ventilation according to the gas area and the gas thickness corresponding to each time.

[0029] As can be seen from the above description, the present application has the beneficial effects that: after obtaining the body information of the user to be measured, the body information of the user to be measured is matched with the set of incident energy reference bases obtained in advance to obtain a corresponding incident energy reference base, and then the user to be measured is exposed to the incident energy reference base to obtain a ventilation image, that is, a suitable incident energy reference base can be selected according to different users to be measured to perform exposure and obtain a more accurate ventilation image, so that the gas thickness and the gas area corresponding to each time are obtained based on the ventilation image and the incident energy reference base, and then accurate ventilation data are obtained; at the same time, the ventilation image is realized based on digital X-ray photography, that is, the ventilation can be measured while the X-ray image is taken.

[0030] Further, the obtaining of the set of calibrated incident energy reference bases comprises: presetting at least one group of image acquisition conditions, taking an image in each image acquisition condition to obtain an incident energy reference base graph corresponding to each image acquisition condition, taking a simulated penetration image in each image acquisition condition to obtain an incident energy penetration graph corresponding to each image acquisition condition, the simulated penetration thicknesses corresponding to different image acquisition conditions being different, obtaining an attenuation rate corresponding to each image acquisition condition according to each incident energy reference base graph and the incident energy penetration graph corresponding thereto, and obtaining a set of incident energy reference bases corresponding to each image acquisition condition according to the incident energy reference base graph, the simulated penetration thickness, and the attenuation rate.

[0031] It can be known from the above description that by setting different image acquisition conditions, calibrating incident energy reference benchmarks and attenuation rates of different image acquisition conditions under different simulated penetration thicknesses, accurate calibration data is obtained, and then the obtained incident energy reference benchmark graph, simulated penetration thickness and attenuation rate are generated into incident energy reference benchmarks, and the incident energy reference benchmark set is integrated, so that after the body information of the user to be measured is obtained, the benchmark matching can be performed based on the accurate incident energy reference benchmark set, the ventilation image exposure is ensured to be performed in the best condition, and the ventilation measurement precision is improved.

[0032] Further, the obtaining of the body information of the user to be measured includes: exposing the body to be measured under a preset exposure condition to obtain an exposure image; and obtaining the body information of the user to be measured according to the brightness of the exposure image.

[0033] It can be known from the above description that the brightness of the exposure image is taken as the information corresponding to the body to be measured, so that the body to be measured can be distinguished based on different brightness.

[0034] Further, the obtaining of the body information of the user to be measured according to the brightness of the exposure image includes: grading the body to be measured according to the brightness of the exposure image to obtain graded thickness information; and the matching of the body information of the user to be measured with the incident energy reference benchmark set to obtain the incident energy reference benchmark corresponding to the body information of the user to be measured includes: further matching according to the graded thickness information in the incident energy reference benchmark set to obtain the corresponding simulated penetration thickness; and obtaining the corresponding incident energy reference benchmark graph and attenuation rate according to the simulated penetration thickness.

[0035] It can be known from the above description that the body to be measured is graded based on the brightness of the exposure image, and the simulated penetration thickness in the incident energy reference benchmark set is matched through the obtained graded thickness information, that is, the thicknesses of different bodies are distinguished through the brightness of the exposure image, and then the corresponding simulated penetration thickness is matched based on the body thickness to obtain the corresponding incident energy reference benchmark graph and attenuation rate, so that the best incident energy reference benchmark can be selected for exposure based on different bodies to be measured, the most accurate ventilation image can be obtained, and the ventilation calculation result is more accurate.

[0036] Further, the obtaining of the ventilation image corresponding to each time in a preset time period according to the incident energy reference benchmark includes: exposing the body to be measured under the incident energy reference benchmark in the preset time period to obtain a body exposure image set; and segmenting each body exposure image in the body exposure image set to obtain the ventilation image corresponding to each time.

[0037] As can be seen from the above description, by exposing the measured shape to the incident energy reference benchmark within a preset time period, a shape exposure image of dynamic change of the shape within a period of time is obtained, and the shape exposure image is segmented, so that the region related to the ventilation calculation in the image is separated, and the ventilation calculation accuracy is improved.

[0038] Further, the segmentation of each shape exposure image in the set of shape exposure images to obtain the ventilation image corresponding to each moment includes: calculating the gray value gradient of the shape exposure image in the first direction and the second direction to obtain an absolute gradient value; determining the number of edges in the shape exposure image according to the absolute gradient value to obtain an edge set; identifying short edges and non-closed edges in the edge set and removing the short edges and non-closed edges from the edge set to obtain target edges; and filling the target edges to obtain the ventilation image.

[0039] As can be seen from the above description, the segmentation method based on edge detection can effectively separate the target image from the shape exposure image, so that more accurate gas area data can be obtained when the ventilation calculation is based on the target image.

[0040] Further, before the calculation of the gradient of the shape exposure image in the first direction and the second direction to obtain the absolute gradient value, the shape exposure image is subjected to smoothing and scaling processing.

[0041] As can be seen from the above description, by performing smoothing and scaling processing on the shape exposure image before calculating the target image, the data amount of the target image is reduced, and the speed of data processing and calculation can be improved.

[0042] Further, the calculation of the gas area corresponding to each moment according to the ventilation image includes: calculating the pixel area corresponding to each moment of the target edge filling region in the ventilation image to obtain the gas area corresponding to each moment.

[0043] As can be seen from the above description, the pixel area corresponding to each moment of the target edge filling region in the ventilation image is accumulated to obtain the accurate gas area.

[0044] Further, the calculation of the gas thickness corresponding to each moment according to the incident energy reference benchmark and the ventilation image includes: obtaining the incident energy corresponding to each moment of the ventilation image, and the incident energy reference benchmark and the attenuation rate corresponding to each moment of the ventilation image; and obtaining the gas thickness corresponding to each moment of the ventilation image according to the incident energy, the incident energy reference benchmark and the attenuation rate.

[0045] From the above description, after obtaining the corresponding incident energy of the ventilation volume image at each moment, the gas thickness corresponding to the ventilation volume image at each moment is obtained according to the relationship between the incident energy and the incident energy reference benchmark and the attenuation rate, and then the accurate gas volume data at each moment is obtained based on the product of the gas thickness at each moment and the gas area.

[0046] Another embodiment of the present application provides a ventilation volume measurement device, comprising:

[0047] A calibration module is configured to obtain a calibrated incident energy reference benchmark set.

[0048] A collection control module is configured to obtain the body information of a user to be measured, match the body information of the user to be measured with the incident energy reference benchmark set, obtain the incident energy reference benchmark corresponding to the body information of the user to be measured, and obtain the ventilation volume image corresponding to each moment in a preset time period according to the incident energy reference benchmark.

[0049] An image processing module is configured to obtain the gas thickness corresponding to each moment according to the incident energy reference benchmark and the ventilation volume image, obtain the gas area corresponding to each moment according to the ventilation volume image, and obtain the ventilation volume according to the gas area corresponding to each moment and the gas thickness.

[0050] The above-mentioned DR-based ventilation volume measurement method and device can be used for the measurement of ventilation volume of different dynamic bodies, such as the measurement of ventilation volume of the lung, and the following will be described through a specific embodiment.

[0051] Embodiment one

[0052] Please refer to Figure 1 A DR-based ventilation volume measurement method, comprising the following steps:

[0053] S1, obtaining a calibrated incident energy reference benchmark set, wherein the incident energy reference benchmark set comprises the calibration of the incident energy benchmark and the calibration of the attenuation rate, and specifically:

[0054] S11, presetting at least one group of image collection conditions, taking an aerial photograph under each image collection condition to obtain the incident energy reference benchmark corresponding to each image collection condition; the image collection condition comprises exposure intensity, and the X-ray is used for irradiation, such as using different voltage (kV) and current (mA) gears for exposure; the aerial photograph is collected in a preset time period, and all the images collected by the aerial photograph are averaged to obtain an average image and the corresponding energy I in , as the incident energy reference benchmark, indicating the image and energy generated when the rays do not pass through the attenuation; the incident energy benchmark and the energy I inPreservation; wherein the image acquisition process is achieved by dynamic DR photography technology;

[0055] S12, simulate penetration shooting under each image acquisition condition to obtain an incident energy penetration map corresponding to each image acquisition condition; the simulated penetration thicknesses corresponding to different image acquisition conditions are different; in an optional embodiment, for the calibration of the attenuation rate, an object with an attenuation rate close to that of human soft tissue is used for measurement, such as polymethylmethacrylate (PMMA) for simulated penetration shooting; different voltages and current positions use different PMMA thicknesses, such as higher voltage using larger PMMA thickness; under a specific position, the corresponding incident energy penetration map and energy I out ;

[0056] S13, obtain the attenuation rate corresponding to each image acquisition condition according to each incident energy reference map and the incident energy penetration map corresponding thereto; the specific attenuation rate is: μ = ln(Iin / Iout) / d, I in is the energy of the incident energy reference map I in corresponding to the position, and d is the PMMA thickness, I out is the energy of the incident energy penetration map I out corresponding to the position; the attenuation rate μ value corresponding to different positions is obtained through the above formula;

[0057] S14, obtain an incident energy reference benchmark set corresponding to each image acquisition condition according to the incident energy reference map, the simulated penetration thickness, and the attenuation rate; that is, the incident energy reference map and the corresponding energy I in , PMMA thickness, and attenuation rate μ value form a group of incident energy reference benchmarks, and multiple groups of incident energy reference benchmarks form the incident energy reference benchmark set.

[0058] S2, obtain the body information of a user to be measured, and match the body information of the user to be measured with the incident energy reference benchmark set to obtain an incident energy reference benchmark corresponding to the body information of the user to be measured; specifically:

[0059] S21, the obtaining of the body information of the user to be measured includes: exposing a body to be measured under a preset exposure condition to obtain an exposure image; for example, irradiating the user to be measured under a specific voltage and current value to obtain the exposure image;

[0060] S22, classifying the body shape to be measured according to the brightness of the exposure image to obtain classified thickness information; different brightness thresholds T1 and T2 are set, when the brightness value is greater than T1, it is represented as large thickness, between T1 and T2, it is represented as medium thickness, and less than T2, it is represented as small thickness; wherein the number of brightness thresholds can be set according to the accuracy requirement, the higher the accuracy, the more the number of brightness thresholds set;

[0061] S23, according to the classified thickness information, further matching in the incident energy reference set to obtain the corresponding simulated penetration thickness; according to the simulated penetration thickness, the corresponding incident energy reference graph and the attenuation rate are obtained; the incident energy reference set also includes the relationship between the brightness value and the thickness, that is, by simulating the penetration shooting under the same preset exposure condition, the corresponding brightness value of the preset exposure condition under different thicknesses is obtained, and the relationship between the brightness value and the simulated penetration thickness is established, that is, the user's body shape can be corresponded to the simulated penetration thickness; so as to obtain the corresponding simulated penetration thickness according to the obtained brightness value, and obtain the corresponding incident energy reference graph and the attenuation rate based on the simulated penetration thickness; in an optional embodiment, the incident energy reference set also presets the exposure aperture condition corresponding to different classified thickness information, that is, the user's body shape is corresponded to different exposure aperture conditions, such as large thickness, the corresponding exposure aperture condition is 120kV and 6mA; such as medium thickness, the corresponding exposure aperture condition is 100kV and 5mA; such as small thickness, the corresponding exposure aperture condition is 80kV and 4mA; after obtaining the corresponding exposure aperture condition, the energy reference graph and the attenuation rate corresponding to the exposure aperture condition are obtained;

[0062] S3, according to the incident energy reference, the ventilation amount image corresponding to each time in a preset time period is obtained; such as constructing the ventilation amount image corresponding to each time into a dynamic image sequence I outi ={0, 1, 2,..., i};

[0063] S4, according to the incident energy reference and the ventilation amount image, the gas thickness corresponding to each time is obtained, and according to the ventilation amount image, the gas area corresponding to each time is obtained;

[0064] S5, according to the gas area and the gas thickness corresponding to each time, the ventilation amount is obtained.

[0065] Example two

[0066] The difference between this embodiment and example one is that the processing method of the ventilation amount image and the calculation method of the ventilation amount are limited, specifically:

[0067] Step S3 includes:

[0068] S31, exposing the object to be measured to the incident energy reference benchmark within a preset time period to obtain a set of object exposure images, i.e. a dynamic image sequence I outi = {0, 1, 2,..., i};

[0069] S32, smoothing and scaling the object exposure images, i.e. smoothing and scaling each exposure image in the dynamic image sequence to reduce the amount of image data to be processed;

[0070] S33, segmenting each of the object exposure images in the set of object exposure images to obtain the ventilation images corresponding to each time point; wherein segmentation can be based on edge detection, deep learning or other image segmentation techniques. In this embodiment, edge detection is used for segmentation as an example, which includes the following steps:

[0071] S331, calculating the gradient of the gray value of the object exposure image in the first direction and the second direction to obtain the absolute gradient value; i.e. calculating the gray value gradient Gx and Gy in the x direction and the y direction of the object exposure image respectively;

[0072]

[0073] S332, determining the number of edges in the object exposure image according to the absolute gradient value to obtain an edge set; another G = |Gx| + |Gy|, when G is greater than a preset threshold, it is considered as an edge;

[0074] S333, identifying short edges and non-closed edges in the edge set and removing the short edges and non-closed edges from the edge set to obtain target edges; i.e. when the number of pixels contained in an edge is less than a number threshold, the edge is considered as a short edge; and when the pixels contained in an edge have only one direction of adjacent edge pixels, the edge is considered as a non-closed edge. After removing the short edges and non-closed edges, edges containing a larger number of pixels and forming a closed space are obtained;

[0075] S334, filling the target edges to obtain the ventilation images; i.e. filling the edges of the closed space; please refer to Figure 2 , for comparison of exposure image processing before and after; it can be seen from the figure that the lung region can be effectively separated after the above processing;

[0076] Step S4 specifically:

[0077] Gas thickness calculation: Obtain the incident energy corresponding to the ventilation volume image at each time step, as well as the incident energy reference map and attenuation rate corresponding to the ventilation volume image at each time step, thus obtaining the corresponding incident energy reference map and energy I. in And attenuation rate μ; based on the incident energy, the incident energy reference map, and the attenuation rate, the gas thickness corresponding to the ventilation image at each moment is obtained, that is, the lung tissue thickness corresponding to each pixel in the lung region is calculated: h i =ln(I in / I outi ) / μ; Using the thickness of the smallest area image frame (i.e., the exposure image with the lowest gas content in the lungs) as a reference h0, calculate the change Δh of the thickness of other frames relative to h0. i =h i -h0, Δh i That is, the thickness of the inhaled gas;

[0078] Gas area calculation: Calculate the pixel area corresponding to the target edge filling area in the ventilation volume map at each time step to obtain the gas area at each time step; identify the two connected regions with the largest area in the image after filling, namely the left and right lung regions; calculate the total area by accumulating the area of ​​individual pixels in the left and right lung regions, such as: pixelSpace*pixelSpace, which is the area of ​​a single pixel, where pixelSpace is the size of a single pixel.

[0079] Step S5 includes: calculating and summing the gas volume for each pixel within the lung region to obtain the volume of inhaled gas.

[0080] V = ∑ x,y∈R V(x,y),

[0081] Where Vi(x, y) = pixelSpace * pixelSpace * Δh i (x, y), calculate the volume for each frame in the image sequence to obtain V = {V0, V1, V2, ..., V...} i};like Figure 3 As shown, the curve of gas volume change over time is obtained. Since the change in tissue volume is caused by the inhaled gas, the airflow velocity can be obtained by differentiating the volume change. i =(V i -V i-1 ) / Δt, where Δt represents the interval between two adjacent frames; for example Figure 4 As shown, the curve of gas flow rate changing with time is obtained; when generating the curve, the curve can also be filtered to make the curve smoother.

[0082] Example 3

[0083] Please refer toFigure 5 A ventilation measurement device comprises:

[0084] A calibration module is configured to obtain a set of calibrated incident energy reference benchmarks; and calibrate the incident energy of the system through the calibration module, so as to solve the incident energy deviation caused by the differences in high voltage, ball stadium, filtration, etc.

[0085] A collection control module is configured to obtain the body information of a user to be measured, match the body information of the user to be measured with the set of incident energy reference benchmarks, obtain the incident energy reference benchmark corresponding to the body information of the user to be measured, and obtain the ventilation image corresponding to each time in a preset time period according to the incident energy reference benchmark; that is, the collection conditions of the dynamic DR system are automatically set according to the body shape of the user to be measured through the collection module, and the dynamic image is collected and stored.

[0086] An image processing module is configured to obtain the gas thickness corresponding to each time according to the incident energy reference benchmark and the ventilation image, obtain the gas area corresponding to each time according to the ventilation image, and obtain the ventilation according to the gas area and the gas thickness corresponding to each time.

[0087] In summary, the ventilation measurement method and device based on DR provided by the application can obtain the body information of a user to be measured, match the body information of the user to be measured with the set of incident energy reference benchmarks obtained in advance, obtain the corresponding incident energy reference benchmark, expose the body to be measured to the incident energy reference benchmark to obtain the ventilation image, select the appropriate incident energy reference benchmark for exposure according to different bodies to be measured, obtain a more accurate ventilation image, obtain the gas thickness and the gas area corresponding to each time based on the ventilation image and the incident energy reference benchmark, and further obtain accurate ventilation data. At the same time, the ventilation image is realized based on digital X-ray photography, that is, the ventilation can be measured at the same time when the X-ray image is taken, and the inspection efficiency is improved.

[0088] The above description is only an embodiment of the application, and does not limit the patent range of the application, and any equivalent transformation or direct or indirect application in the related technical field based on the content of the specification and the drawings is also included in the patent protection range of the application.

Claims

1. A method of measuring ventilation based on DR, characterized in that, The method comprises the steps of: obtaining a set of reference incident energy standards; obtaining body information of a user to be measured, and matching the body information of the user to be measured with the set of reference incident energy standards to obtain reference incident energy standards corresponding to the body information of the user to be measured; obtaining a ventilation amount image corresponding to each time within a preset time period according to the reference incident energy standards; obtaining a gas thickness corresponding to each time according to the reference incident energy standards and the ventilation amount image, and obtaining a gas area corresponding to each time according to the ventilation amount image; obtaining a ventilation amount according to the gas area and the gas thickness corresponding to each time.

2. The method of claim 1, wherein, The method comprises the steps of: obtaining a set of reference incident energy standards; obtaining a set of at least one image acquisition condition, and obtaining an incident energy reference graph corresponding to each image acquisition condition by image aerial photography under each image acquisition condition; obtaining an incident energy penetration graph corresponding to each image acquisition condition by simulated penetration photography under each image acquisition condition; the simulated penetration thicknesses corresponding to different image acquisition conditions are different; obtaining an attenuation rate corresponding to each image acquisition condition according to each incident energy reference graph and the incident energy penetration graph corresponding thereto; 3. The method of claim 1, wherein, obtaining a set of reference incident energy standards corresponding to each image acquisition condition according to the incident energy reference graph, the simulated penetration thickness, and the attenuation rate. The method comprises the steps of: exposing a body to be measured under a preset exposure condition to obtain an exposure image; 4. The method of claim 3, wherein, obtaining body information of the user to be measured according to the brightness of the exposure image. The method comprises the steps of: grading the body to be measured according to the brightness of the exposure image to obtain graded thickness information; The method comprises the steps of: matching the body information of the user to be measured in the set of reference incident energy standards to obtain corresponding simulated penetration thicknesses according to the graded thickness information; 5. The method of claim 1, wherein, obtaining a corresponding incident energy reference graph and an attenuation rate according to the simulated penetration thickness. The method comprises the steps of: exposing the body to be measured to the reference incident energy within a preset time period to obtain a set of body exposure images; 6. The method of claim 5, wherein, segmenting each body exposure image in the set of body exposure images to obtain a ventilation amount image corresponding to each time. The method comprises the steps of: calculating the gradient of the gray value of the body exposure image in a first direction and a second direction to obtain an absolute gradient value; determining the number of edges in the body exposure image according to the absolute gradient value to obtain an edge set; Identifying short edges and non-closed edges in the edge set and removing the short edges and non-closed edges from the edge set to obtain target edges; Filling the target edges to obtain the ventilation map image.

7. The method of claim 6, wherein, The calculation of the gradient of the body exposure image in the first direction and the second direction to obtain the absolute gradient value includes: Smoothing and scaling the body exposure image.

8. The method of claim 6, wherein, The obtaining of the gas area corresponding to each time point according to the ventilation map image includes: Calculating the pixel area corresponding to the target edge filling area in the ventilation map at each time point to obtain the gas area corresponding to each time point.

9. The method of claim 2, wherein, The obtaining of the gas thickness corresponding to each time point according to the incident energy reference benchmark and the ventilation map image includes: Obtaining the incident energy corresponding to each time point of the ventilation map image, and the incident energy reference benchmark and the decay rate corresponding to each time point of the ventilation map image; Obtaining the gas thickness corresponding to each time point of the ventilation map image according to the incident energy, the incident energy reference benchmark and the decay rate.

10. A DR-based ventilation measurement device, characterized by It includes: The calibration module is used for obtaining a set of calibrated incident energy reference benchmarks; The acquisition control module is used for obtaining the body information of the user to be measured, matching the body information of the user to be measured with the set of incident energy reference benchmarks to obtain the incident energy reference benchmark corresponding to the body information of the user to be measured, and obtaining the ventilation map image corresponding to each time point in a preset time period according to the incident energy reference benchmark; The image processing module is used for obtaining the gas thickness corresponding to each time point according to the incident energy reference benchmark and the ventilation map image, obtaining the gas area corresponding to each time point according to the ventilation map image, and obtaining the ventilation according to the gas area corresponding to each time point and the gas thickness.

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