Method, device, equipment and storage medium for determining volume of small airway lesion area

Abstract

The present invention discloses a method, device, equipment and storage medium for determining the volume of a small airway lesion area, the method comprising: acquiring a lung image, and determining the number of layers, scanning layer thickness and inter-layer spacing of the lung image; using the lung image to identify a small airway lesion area; performing gridding processing on the small airway lesion area to obtain the grid area of ​​the small airway lesion area; and determining the volume of the small airway lesion area based on the number of layers, the scanning layer thickness, the inter-layer spacing and the networked area. The present invention can achieve the determination of the volume of a small airway lesion area and can achieve quantitative analysis of small airway lesions.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a method, device, equipment and storage medium for determining the volume of a small airway lesion area. Background Art

[0002] Clinically, small bronchioles with an inner diameter of less than 2 mm are usually called small airways. Small airways have the characteristics of low airflow resistance but easy obstruction. During quiet inhalation, air enters the narrow nasopharynx and generates vortices. Since small airways have no cartilage support, after they are separated from the fibrous sheath and embedded in the lung tissue, the patency of the lumen is not like that of cartilaginous airways, and they are easily affected by changes in chest pressure.

[0003] Studies have shown that in COPD, the relationship between small airway lesions and emphysema destruction indicates that the shrinkage and disappearance of terminal bronchitis precedes the destruction of emphysema in COPD, so the lesions of small airway lesions precede emphysema. The literature provides a calculation model for the mutual transformation of normal areas, small airway lesion areas, and emphysema areas. If small airway lesions are detected as early as possible, the formation of emphysema in COPD can be avoided to a certain extent. If the small airways become fibrotic, deformed, narrowed, or even closed, the function of the small airways is irreversible.

[0004] At present, due to the small diameter of small airways, it is difficult to observe and measure small airways, especially difficult to quantitatively analyze small airway lesions. Therefore, how to achieve quantitative analysis of small airway lesions has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The main purpose of the present invention is to provide a method, device, equipment and storage medium for determining the volume of a small airway lesion area, aiming to solve the problem that it is difficult to quantitatively analyze small airway lesions.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a method for determining the volume of a small airway lesion area, comprising:

[0007] Acquire a lung image, and determine the number of layers, scanning layer thickness, and layer spacing of the lung image;

[0008] identifying a small airway lesion area using the lung image;

[0009] Performing grid processing on the small airway lesion area to obtain a grid area of ​​the small airway lesion area;

[0010] The volume of the small airway lesion region is determined based on the number of layers, the scanning layer thickness, the layer spacing and the networked area.

[0011] Optionally, the gridding process is performed on the small airway lesion region to obtain the gridded area of ​​the small airway lesion region, including:

[0012] determining the margins of the small airway lesion area;

[0013] Drawing a grid in the small airway lesion area, and when the drawn network touches the edge, refining the grid;

[0014] When the number of grids is greater than or equal to a preset number, the refinement process is stopped, and the sum of the areas of the grids is determined as the gridded area of ​​the small airway lesion region.

[0015] Optionally, drawing a grid in the small airway lesion area and refining the grid when the drawn grid touches the edge includes:

[0016] Draw a first standard shape grid in the small airway lesion area, and extend the first standard shape grid toward the edge;

[0017] When a number of set points of the first standard shape grid touches the edge, the first standard shape grid is stopped from being extended, and a second standard shape grid is generated outside the first standard shape grid, wherein a number of set points and an area of ​​the second standard shape area are respectively smaller than a number of set points and an area of ​​the first standard shape area;

[0018] The second standard shape mesh is extended toward the edge.

[0019] Optionally, determining the volume of the small airway lesion area based on the number of layers, the scanning layer thickness, the layer spacing and the grid area includes:

[0020] Using the grid area of ​​the small airway lesion region of two adjacent layers, the scanning layer thickness, and the layer spacing, a subvolume formed by the small airway lesion region of two adjacent layers is obtained;

[0021] The sum of the sub-volumes corresponding to the number of layers is calculated to obtain the volume of the small airway lesion area.

[0022] Optionally, the lung image includes a full inspiratory phase lung image and a full expiratory phase lung image, and identifying the small airway lesion area using the lung image includes:

[0023] respectively registering the full inspiratory phase lung image and the full expiratory phase lung image;

[0024] Comparing the first computed tomography image CT value of the registered full inspiratory phase lung image with the threshold set in the inspiratory phase, and comparing the second CT value of the registered full expiratory phase lung image with the threshold set in the expiratory phase;

[0025] An image region where the first CT value is less than a threshold set in the inspiratory phase and the second CT value is less than a threshold set in the expiratory phase is determined as a small airway lesion region.

[0026] Furthermore, the first standard shape grid is located at the geometric center of the small airway lesion area. Before drawing the first standard shape grid in the small airway lesion area, the method further includes:

[0027] Acquire a plurality of reference points set in the small airway lesion region;

[0028] Calculate the distances from each reference point to the edge;

[0029] According to the several distances, the geometric center of the small airway lesion area is determined.

[0030] Optionally, determining the geometric center of the small airway lesion area according to the plurality of distances includes:

[0031] respectively calculating the differences between the plurality of distances;

[0032] Count the number of distance differences corresponding to each reference point that are less than a preset threshold;

[0033] The positions of the reference points whose number is greater than or equal to the preset number are determined as the geometric center of the small airway lesion area.

[0034] In a second aspect, the present invention provides a device for determining the volume of a small airway lesion area, comprising:

[0035] An acquisition module, used for acquiring lung images;

[0036] A determination module, used to determine the number of layers, scanning layer thickness and layer spacing of the lung image;

[0037] An identification module, used to identify a small airway lesion area using the lung image;

[0038] A processing module, used for performing grid processing on the small airway lesion area to obtain a grid area of ​​the small airway lesion area;

[0039] The determination module is used to determine the volume of the small airway lesion area based on the number of layers, the scanning layer thickness, the layer spacing and the networked area.

[0040] Optionally, the processing module includes:

[0041] A determination unit, used to determine the edge of the small airway lesion area;

[0042] A processing unit, configured to draw a grid in the small airway lesion region, and to refine the grid when the drawn grid touches the edge;

[0043] The determination unit is further configured to stop the refinement process when the number of grids is greater than or equal to a preset number, and determine the sum of the areas of each grid as the gridded area of ​​the small airway lesion region.

[0044] The processing unit is used to draw a first standard shape grid in the small airway lesion area, and extend the first standard shape grid toward the edge;

[0045] When a number of set points of the first standard shape grid touches the edge, the first standard shape grid is stopped from being extended, and a second standard shape grid is generated outside the first standard shape grid, wherein a number of set points and an area of ​​the second standard shape area are respectively smaller than a number of set points and an area of ​​the first standard shape area;

[0046] The second standard shape mesh is extended toward the edge.

[0047] Optionally, the determination module is used to obtain the sub-volume formed by two adjacent layers of small airway lesion areas using the grid area of ​​the small airway lesion areas of two adjacent layers, the scanning layer thickness, and the layer spacing; and calculate the sum of the sub-volumes corresponding to the number of layers to obtain the volume of the small airway lesion area.

[0048] Optionally, the recognition module is used to register the full inhalation phase lung image and the full expiratory phase lung image respectively;

[0049] Comparing the first computed tomography image CT value of the registered full inspiratory phase lung image with the threshold set in the inspiratory phase, and comparing the second CT value of the registered full expiratory phase lung image with the threshold set in the expiratory phase;

[0050] An image region where the first CT value is less than a threshold set in the inspiratory phase and the second CT value is less than a threshold set in the expiratory phase is determined as a small airway lesion region.

[0051] Optionally, the device further comprises:

[0052] An acquisition module, used for acquiring a plurality of reference points set in the small airway lesion area;

[0053] A calculation module, used for calculating a number of distances from each reference point to the edge;

[0054] The determination module is further used to determine the geometric center of the small airway lesion area based on the several distances.

[0055] Optionally, the determination module is specifically configured to respectively calculate the differences between the plurality of distances;

[0056] Count the number of distance differences corresponding to each reference point that are less than a preset threshold;

[0057] The positions of the reference points whose number is greater than or equal to the preset number are determined as the geometric center of the small airway lesion area.

[0058] In a third aspect, the present invention further proposes a device for determining the volume of a small airway lesion area, the device comprising: a memory, a processor, and a small airway lesion area volume determination program stored in the memory and executable on the processor, the small airway lesion area volume determination program being executed by the processor to perform the steps of the small airway lesion area volume determination method.

[0059] In a fourth aspect, the present invention further proposes a computer-readable storage medium, on which a volume determination program for a small airway lesion area is stored, and when the volume determination program for a small airway lesion area is executed by a processor, the steps of the method for determining the volume of a small airway lesion area are implemented.

[0060] The present invention provides a method, device, equipment and storage medium for determining the volume of a small airway lesion area. Compared with the current difficulty in quantitatively analyzing small airway lesions, the present invention can obtain a lung image, and after determining the number of layers, scanning layer thickness and layer spacing of the lung image; the lung image can be used to identify the small airway lesion area; the small airway lesion area is gridded to obtain the grid area of ​​the small airway lesion area; based on the number of layers, the scanning layer thickness, the layer spacing and the networked area, the volume of the small airway lesion area is determined, and the quantitative analysis of the small airway lesions can be achieved through the volume of the small airway lesion area. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the structure of the hardware operating environment involved in the embodiment of the present invention;

[0062] Figure 2 A schematic flow chart of a method for determining the volume of a small airway lesion area according to an embodiment of the present invention;

[0063] Figure 3 Schematic diagram of functional modules of a preferred embodiment of the device for determining the volume of a small airway lesion area of ​​the present invention.

[0064] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0065] 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.

[0066] like Figure 1 As shown, Figure 1 It is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention.

[0067] It should be noted that the volume determination method of the small airway lesion area provided in the embodiment of the present invention can be used for quantitative analysis of small airway lesions. The execution subject of the method can be any small airway lesion area volume determination device. For example, the volume determination method of the small airway lesion area can be executed by a terminal device or a server or other processing device, wherein the terminal device can be a user equipment (User Equipment, UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc., and no specific restrictions are made here.

[0068] like Figure 1 As shown, the volume determination device of the small airway lesion area may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0069] Those skilled in the art will understand that Figure 1 The device structure shown in the figure does not constitute a limitation on the device for determining the volume of the small airway lesion area, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0070] like Figure 1As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a volume determination program for a small airway lesion region. The operating system is a program for managing and controlling the hardware and software resources of the device, and supports the operation of the volume determination program for a small airway lesion region and other software or programs.

[0071] exist Figure 1 In the device shown, the user interface 1003 is mainly used for data communication with the client; the network interface 1004 is mainly used for establishing a communication connection with the server; and the processor 1001 can be used to call the volume determination program of the small airway lesion area stored in the memory 1005, and execute the volume determination method of the small airway lesion area of ​​the embodiment of the present invention.

[0072] Reference Figure 2 , Figure 2 A schematic flow chart of a method for determining the volume of a small airway lesion area provided in an embodiment of the present invention.

[0073] S10: Acquire a lung image, and determine the number of layers, scanning layer thickness, and layer spacing of the lung image;

[0074] S20: using the lung image to identify a small airway lesion area;

[0075] S30: performing grid processing on the small airway lesion area to obtain a grid area of ​​the small airway lesion area;

[0076] S40: Determine the volume of the small airway lesion region based on the number of layers, the scanning layer thickness, the layer spacing and the networked area.

[0077] In some possible implementations, the embodiments of the present invention can obtain a lung image by shooting CT (Computed Tomography), and the lung image includes at least one of a full inspiratory phase lung image and a full expiratory phase lung image. The full inspiratory phase lung image has the same number of layers, the scanning layer thickness, and the inter-layer spacing as the full expiratory phase lung image. In an embodiment of the present invention, the full inspiratory phase lung image and the full expiratory phase lung image are lung images of a patient, and the full inspiratory phase lung image is a lung image taken by an influencing device during deep inhalation while keeping the lung air volume at a maximum. Similarly, the full expiratory phase lung image is a lung image taken by an influencing device during deep exhalation while keeping the lung air volume at a minimum.

[0078] It should be noted that the number of layers, scanning layer thickness and inter-layer spacing of the lung image are all information inherent in the lung image, such as the lung image can be a DICOM image. Specifically, the number of layers, scanning layer thickness and inter-layer spacing of the image determined by the full inspiratory phase lung image or the full expiratory phase lung image are all information inherent in the full inspiratory phase lung image or the full expiratory phase lung image, such as the full inspiratory phase lung image or the full expiratory phase lung image can be a DICOM image. DICOM (Digital Imaging and Communications in Medicine) is digital imaging and communications in medicine, and is an international standard for medical images and related information (ISO 12052). It defines a medical image format that can be used for data exchange and whose quality can meet clinical needs. The number of layers, scanning layer thickness and inter-layer spacing of the image are obtained by reading the DICOM information of the full inspiratory phase lung image or the full expiratory phase lung image.

[0079] In an embodiment of the present invention, in order to identify the small airway lesion area, the step 20, the lung image includes a full inspiratory phase lung image and a full expiratory phase lung image, and the use of the lung image to identify the small airway lesion area includes: respectively aligning the full inspiratory phase lung image and the full expiratory phase lung image; comparing the first computed tomography CT value of the aligned full inspiratory phase lung image with the inspiratory phase set threshold, and comparing the second CT value of the aligned full expiratory phase lung image with the expiratory phase set threshold; determining the image area with a first CT value less than the inspiratory phase set threshold and a second CT value less than the expiratory phase set threshold as a small airway lesion area.

[0080] Specifically, the method for registering the full inspiratory phase lung image and the full expiratory phase lung image can use an elastic registration algorithm or utilize the VGG network (VGG-net) in deep learning for registration. The embodiment of the present invention does not limit the specific registration algorithm. The inspiratory phase setting threshold can be set to -950HU, and the expiratory phase setting threshold can be set to -856HU. If the CT value of the full inspiratory phase lung image after registration is less than the inspiratory phase setting threshold -950HU, and the CT value of the full expiratory phase lung image after registration is less than the expiratory phase setting threshold -856HU, it is considered that there are small airway lesions in this area; otherwise, it is considered that there are no small airway lesions in this area.

[0081] In an embodiment of the present invention, in order to determine the grid area of ​​the small airway lesion area, the step 30 performs gridding processing on the small airway lesion area to obtain the grid area of ​​the small airway lesion area, including: determining the edge of the small airway lesion area; drawing a grid in the small airway lesion area, and when the drawn network touches the edge, refining the grid; when the number of grids is greater than or equal to a preset number, stopping the refinement processing, and determining the sum of the areas of each grid as the gridded area of ​​the small airway lesion area.

[0082] Specifically, a grid is drawn in the small airway lesion area, and when the drawn network touches the edge, the grid is refined, including: drawing a first standard shape grid in the small airway lesion area, and extending the first standard shape grid toward the edge; when a number of set points of the first standard shape grid touch the edge, stopping the extension of the first standard shape grid, and generating a second standard shape grid outside the first standard shape grid, wherein a number of set points and an area of ​​the second standard shape area are respectively smaller than a number of set points and an area of ​​the first standard shape area; and extending the second standard shape grid toward the edge.

[0083] For example, if the first specification shape is a circle, a number of set points can be evenly set on the circumference of the circle, such as 20 set points. When a number of set points of the first specification shape touch the edge of the small airway lesion area, the first specification shape stops extending and generates a second specification shape outside the specification shape; the second specification shape can also be selected from any of a circle, an ellipse, a rectangle, and a square, but the second specification shape is smaller than the first specification shape to achieve the purpose of fine division. For the setting of the value of the set number, those skilled in the art can set it by themselves according to the accuracy requirements.

[0084] In an embodiment of the present invention, the step 40, determining the volume of the small airway lesion area based on the number of layers, the scanning layer thickness, the layer spacing and the grid area, includes: using the grid area of ​​the small airway lesion area of ​​two adjacent layers and the scanning layer thickness and the layer spacing to obtain the sub-volume formed by the small airway lesion area of ​​two adjacent layers; calculating the sum of the sub-volumes corresponding to the number of layers to obtain the volume of the small airway lesion area.

[0085] The sub-volume formed by the two adjacent layers of small airway lesion areas is obtained by using the grid area corresponding to each adjacent two layers of small airway lesion areas, as well as the inter-layer spacing and layer thickness, and the volume of the small airway lesion area is obtained by using the sum of the sub-volumes formed by all the adjacent two layers of small airway lesion areas. Among them, the structure formed by the adjacent two layers of lung area can be regarded as a prism, and the area of ​​the upper and lower bottom surfaces of the prism is the grid area corresponding to the small airway lesion area. The height of the prism can be determined by the inter-layer spacing and the layer thickness. For example, if the number of layers is N, the height of the prism formed by the first and second layers of small airway lesion areas can be the sum of the layer thickness*2 and the inter-layer spacing, and the height of the prism formed by the remaining two adjacent layers of small airway lesion areas can be the sum of the layer thickness and the inter-layer spacing. The sub-volume of the small airway lesion area formed by the adjacent layers can be determined based on the upper and lower bottom areas and the height. Then, the volume of the small airway lesion area can be obtained by using the sum of the sub-volumes. In other words, since there may be multiple small airway lesion areas, the volume of the small airway lesion area is the total volume of all small airway lesion areas.

[0086] For the embodiment of the present invention, in order to ensure the accuracy of the grid area of ​​the small airway lesion area, the first shape grid can be drawn starting from the geometric center of the small airway lesion area, that is, the first specification shape grid is located at the geometric center of the small airway lesion area. Before drawing the first specification shape grid in the small airway lesion area, the method also includes: obtaining a number of reference points set in the small airway lesion area; calculating a number of distances from each reference point to the edge; and determining the geometric center of the small airway lesion area based on the several distances.

[0087] In an embodiment of the present invention, the specific method of respectively calculating the distances from the plurality of points to the edge to obtain the plurality of distances from each point to the edge is: respectively emitting to the edge in the form of a plurality of rays with the plurality of points as the center, making a plurality of marks when the plurality of rays reach the edge or intersect with the edge, and the distances from the plurality of points to the plurality of marks are the plurality of distances from each point to the edge. The plurality of rays may be equally spaced or unequally spaced.

[0088] For example, the plurality of points are 10 points, and the positions of the 10 points are within the small airway lesion area. The 10 points are calculated as the center and emitted to the edge in the form of a plurality of rays (100 rays). When the plurality of rays reach the edge or intersect with the edge, a plurality of marks (100 marks) are made; the distance between each point and the plurality of marks is a plurality of distances from each point to the edge.

[0089] Specifically, a point is defined as OX, X represents the nth point, X=1 represents the first point among the 10 points, and a point is emitted to the edge in the form of 100 rays. At this time, the number of markers is 100, namely X1 to X100; the number of distances from a point OX to X1 to X100 on the edge is 100, and the geometric center of the small airway lesion area is determined according to the 100 distances of each of the 10 points.

[0090] It should be noted that the determination of the geometric center of the small airway lesion area based on the several distances includes: calculating the difference between the several distances respectively; counting the number of distance differences corresponding to each reference point that is less than a preset threshold; and determining the position of the reference points whose number is greater than or equal to the preset number as the geometric center of the small airway lesion area. Specifically, the difference between the several distances from each point to the edge is calculated respectively; the difference between the several distances of a certain point is compared with a set value, and if the difference is less than the set value, it is accumulated; when the accumulated number is greater than or equal to the preset number, the position of the certain point is the geometric center of the small airway lesion area.

[0091] For example, taking one of the several points as an example, 100 rays centered on this point are emitted toward the edge, and the number of distances from this point to the edge is 100. The difference between the 100 is calculated, and each difference is compared with the set value. If the difference is less than the set value, accumulation is performed; when the accumulated number is greater than or equal to the preset number, the position of this point is the geometric center of the small airway lesion area. For the setting of the set value and the preset number, those skilled in the art can set it according to the number of distances from the point to the edge and the accuracy required, such as the set value can be 0.5-1mm; when the number of distances from the point to the edge is 100, the preset number can be 80.

[0092] In an embodiment of the present invention, if the positions of multiple points (such as 2 points) are determined to be the geometric center of the small airway lesion area, the cumulative number of the multiple points is compared, and the one with a larger cumulative number is the geometric center of the small airway lesion area.

[0093] If there are multiple points such as 2 points, namely the first point and the second point, if the positions of the first point and the second point are both determined to be the geometric center of the small airway lesion area, then compare the cumulative number of the first point and the cumulative number of the second point. If the cumulative number of the first point is greater than the cumulative number of the second point, the position of the first point is the geometric center of the small airway lesion area.

[0094] In an embodiment of the present invention, the specific method for determining the geometric center of the small airway lesion area based on a number of distances from each point to the edge is: respectively calculating the difference between a number of distances from each point to the edge; comparing the difference between the several distances of a certain point with a set value, and if the difference is less than the set value, accumulating them; when the accumulated number is greater than or equal to a preset number, the position of the certain point is the geometric center of the small airway lesion area.

[0095] In some other embodiments of the present invention, the method for determining the geometric center of the small airway lesion area can also be: shrinking the edge of the small airway lesion area according to a first preset scale to obtain a first edge; selecting a plurality of first reference points on the first edge, and fitting the first reference points to form a first circle; in response to the radius of the first circle being greater than a radius threshold, shrinking the first edge according to a second preset scale until the radius of the circle formed by the plurality of second reference points selected on the shrunken edge is less than the radius threshold; and determining the geometric center of the small airway lesion area using the position mean of the plurality of second reference points or the center of the circle formed by the second reference points. The first preset scale is greater than the second preset scale, such as the first preset scale can be 80% and the second preset scale can be 10%, but this is not a specific limitation of the embodiments of the present invention.

[0096] That is to say, in an embodiment of the present invention, when a small airway lesion area is determined, the edge of the small airway lesion area can be determined to form an edge. Then, the edge can be reduced according to a first preset scale to obtain a first edge. Then, a number of first reference points can be selected from the first edge according to a first rule, wherein the edge of the small airway lesion area can be regarded as consisting of multiple points, and the corresponding first edge can also include multiple points. The first rule can include selecting a number of first reference points according to a preset number of interval points. For example, the preset number of interval points can be 10, and a first reference point can be selected every 10 points on the first edge, wherein the preset number of interval points is not specifically limited. After selecting the first reference point, the first reference point can be curve fitted to form a first circle, and then the radius of the first circle can be determined, wherein the curve fitting method can be the least squares method, but it is not limited to the present invention. If the radius of the first circle is less than or equal to the radius threshold, the center of the first circle can be used as the geometric center of the small airway lesion area, or the mean position of the first reference point can be determined as the geometric center of the small airway lesion area.

[0097] If the radius of the first circle is greater than the radius threshold, it means that the first edge needs to be further reduced to reduce the error. At this time, it can be reduced according to the second preset scale, and the second preset scale is smaller than the first preset scale. When the first edge is reduced to form a second edge (at least one), several second reference points can be selected on the second edge. Similarly, the second reference points can be used to fit a circle (second circle), and it is determined whether the second edge needs to be reduced according to the above rules. If the radius of the second circle fitted by the second reference point is greater than the radius threshold, the second edge is further reduced according to the second preset scale. Conversely, if the radius of the second circle is less than or equal to the radius threshold, the center of the second circle or the position mean of the second reference point can be determined as the geometric center of the small airway lesion area.

[0098] In addition, the embodiment of the present invention also provides a volume determination device for a small airway lesion area, referring to Figure 3 , the volume determination device of the small airway lesion area comprises:

[0099] An acquisition module 10, used for acquiring a lung image;

[0100] A determination module 20, used to determine the number of slices, scanning slice thickness and slice spacing of the lung image;

[0101] An identification module 30, configured to identify a small airway lesion area using the lung image;

[0102] A processing module 40 is used to perform grid processing on the small airway lesion area to obtain a grid area of ​​the small airway lesion area;

[0103] The determination module 20 is used to determine the volume of the small airway lesion area based on the number of layers, the scanning layer thickness, the layer spacing and the networked area.

[0104] Optionally, the processing module 40 includes:

[0105] A determination unit, used to determine the edge of the small airway lesion area;

[0106] A processing unit, configured to draw a grid in the small airway lesion region, and to refine the grid when the drawn grid touches the edge;

[0107] The determination unit is further configured to stop the refinement process when the number of grids is greater than or equal to a preset number, and determine the sum of the areas of each grid as the gridded area of ​​the small airway lesion region.

[0108] The processing unit is used to draw a first standard shape grid in the small airway lesion area, and extend the first standard shape grid toward the edge;

[0109] When a number of set points of the first standard shape grid touches the edge, the first standard shape grid is stopped from being extended, and a second standard shape grid is generated outside the first standard shape grid, wherein a number of set points and an area of ​​the second standard shape area are respectively smaller than a number of set points and an area of ​​the first standard shape area;

[0110] The second standard shape mesh is extended toward the edge.

[0111] Optionally, the determination module is used to obtain the sub-volume formed by two adjacent layers of small airway lesion areas using the grid area of ​​the small airway lesion areas of two adjacent layers, the scanning layer thickness, and the layer spacing; and calculate the sum of the sub-volumes corresponding to the number of layers to obtain the volume of the small airway lesion area.

[0112] Optionally, the recognition module is used to register the full inhalation phase lung image and the full expiratory phase lung image respectively;

[0113] Comparing the first computed tomography image CT value of the registered full inspiratory phase lung image with the threshold set in the inspiratory phase, and comparing the second CT value of the registered full expiratory phase lung image with the threshold set in the expiratory phase;

[0114] An image region where the first CT value is less than a threshold set in the inspiratory phase and the second CT value is less than a threshold set in the expiratory phase is determined as a small airway lesion region.

[0115] Optionally, the device further comprises:

[0116] An acquisition module, used for acquiring a plurality of reference points set in the small airway lesion area;

[0117] A calculation module, used for calculating a number of distances from each reference point to the edge;

[0118] The determination module is further used to determine the geometric center of the small airway lesion area based on the several distances.

[0119] Optionally, the determination module 20 is specifically configured to respectively calculate the differences between the plurality of distances;

[0120] Count the number of distance differences corresponding to each reference point that are less than a preset threshold;

[0121] The positions of the reference points whose number is greater than or equal to the preset number are determined as the geometric center of the small airway lesion area.

[0122] In addition, an embodiment of the present invention further proposes a computer-readable storage medium, on which a volume determination program for a small airway lesion area is stored. When the volume determination program for a small airway lesion area is executed by a processor, the steps of the method for determining the volume of a small airway lesion area described below are implemented.

[0123] The various embodiments of the device for determining the volume of a small airway lesion area and the computer-readable storage medium of the present invention can all refer to the various embodiments of the method for determining the volume of a small airway lesion area of ​​the present invention, and will not be described in detail here.

[0124] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0125] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0126] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0127] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for determining the volume of a small airway lesion area, characterized in that: include: Acquire a lung image, and determine the number of layers, scanning layer thickness, and layer spacing of the lung image; identifying a small airway lesion area using the lung image; Performing grid processing on the small airway lesion area to obtain a grid area of ​​the small airway lesion area; Determining the volume of the small airway lesion area based on the number of layers, the scanning layer thickness, the layer spacing and the grid area; The gridding process is performed on the small airway lesion region to obtain the grid area of ​​the small airway lesion region, including: determining the margins of the small airway lesion area; Drawing a grid in the small airway lesion area, and when the drawn network touches the edge, refining the grid; When the number of grids is greater than or equal to a preset number, the refinement process is stopped, and the sum of the areas of the grids is determined as the grid area of ​​the small airway lesion area; Drawing a grid in the small airway lesion area and refining the grid when the drawn grid touches the edge includes: Draw a first standard shape grid in the small airway lesion area, and extend the first standard shape grid toward the edge; When the set points of the first standard shape grid touch the edge, stop extending the first standard shape grid, and generate a second standard shape grid outside the first standard shape grid, wherein the set points and area of ​​the second standard shape grid are respectively smaller than the set points and area of ​​the first standard shape grid; Performing an extension process on the second standard shape grid toward the edge; The determining the volume of the small airway lesion area based on the number of layers, the scanning layer thickness, the layer spacing and the grid area includes: Using the grid area of ​​the small airway lesion region of two adjacent layers, the scanning layer thickness, and the layer spacing, a subvolume formed by the small airway lesion region of two adjacent layers is obtained; The sum of the sub-volumes corresponding to the number of layers is calculated to obtain the volume of the small airway lesion area.

2. The method according to claim 1, characterized in that The lung image includes a full inhalation phase lung image and a full expiratory phase lung image, and the method of using the lung image to identify the small airway lesion area includes: respectively registering the full inspiratory phase lung image and the full expiratory phase lung image; Comparing the first computed tomography image CT value of the registered full inspiratory phase lung image with the threshold set in the inspiratory phase, and comparing the second CT value of the registered full expiratory phase lung image with the threshold set in the expiratory phase; An image region where the first CT value is less than a threshold set in the inspiratory phase and the second CT value is less than a threshold set in the expiratory phase is determined as a small airway lesion region.

3. The method according to claim 1, characterized in that The first standard shape grid is located at the geometric center of the small airway lesion area. Before drawing the first standard shape grid in the small airway lesion area, the method further includes: Acquire a plurality of reference points set in the small airway lesion region; Calculate the distances from each reference point to the edge; The geometric center of the small airway lesion area is determined according to the several distances.

4. The method according to claim 3, characterized in that Determining the geometric center of the small airway lesion area according to the plurality of distances includes: respectively calculating the differences between the plurality of distances; Count the number of distance differences corresponding to each reference point that are less than a preset threshold; The positions of the reference points whose number is greater than or equal to the preset number are determined as the geometric center of the small airway lesion area.

5. A device for determining the volume of a small airway lesion area, characterized in that: include: An acquisition module, used for acquiring lung images; A determination module, used to determine the number of layers, scanning layer thickness and layer spacing of the lung image; An identification module, used to identify a small airway lesion area using the lung image; A processing module, used for performing grid processing on the small airway lesion area to obtain a grid area of ​​the small airway lesion area; The determination module is used to determine the volume of the small airway lesion area based on the number of layers, the scanning layer thickness, the layer spacing and the grid area; The processing module comprises: A determination unit, used to determine the edge of the small airway lesion area; A processing unit, configured to draw a grid in the small airway lesion region, and to refine the grid when the drawn grid touches the edge; The determining unit is further configured to stop the refinement process when the number of grids is greater than or equal to a preset number, and determine the sum of the areas of each grid as the grid area of ​​the small airway lesion region; The processing unit is used to draw a first standard shape grid in the small airway lesion area, and extend the first standard shape grid toward the edge; when a number of set points of the first standard shape grid touch the edge, stop extending the first standard shape grid, and generate a second standard shape grid outside the first standard shape grid, wherein the number of set points and the area of ​​the second standard shape grid are respectively smaller than the number of set points and the area of ​​the first standard shape grid; and extend the second standard shape grid toward the edge; The determination module is also used to obtain the sub-volume formed by two adjacent layers of small airway lesion areas using the grid area of ​​two adjacent layers of small airway lesion areas, the scanning layer thickness, and the layer spacing; and calculate the sum of the sub-volumes corresponding to the number of layers to obtain the volume of the small airway lesion area.

6. A device for determining the volume of a small airway lesion area, characterized in that: The device for determining the volume of a small airway lesion area comprises: a memory, a processor, and a small airway lesion area volume determination program stored in the memory and executable on the processor. When the small airway lesion area volume determination program is executed by the processor, the steps of the small airway lesion area volume determination method as described in any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a volume determination program for a small airway lesion area, and when the volume determination program for a small airway lesion area is executed by a processor, the steps of the method for determining the volume of a small airway lesion area according to any one of claims 1 to 4 are implemented.

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