Hip joint imaging method and device

Abstract

The invention provides a hip joint imaging method and system, and the method comprises the steps: obtaining a three-dimensional model of a hip joint part and a layer-by-layer CT original image in a Z-axis direction, and determining the relative position of a metal implant at the hip joint part according to the three-dimensional model; according to the relative position, a first CT original image corresponding to the maximum cross section of the metal implant in the Z-axis direction is determined; according to the three-dimensional model, obtaining an actual contour of the metal implant in the Z-axis direction when the metal implant has the maximum cross section, and determining a display contour of the metal implant in the first CT original image; determining influence line segments around the metal implant in different directions, and determining influence ranges of the metal implant on the first CT original image in different directions according to the actual contour and the display contour; and optimizing the first CT original image according to the influence range and the influence line segment to reduce artifacts.

Description

Technical Field

[0001] The present invention belongs to the technical field of hip joint imaging, and particularly relates to a hip joint imaging method and device. Background Art

[0002] The hip joint is one of the largest joints in the human body. It is located where the lower limbs connect to the trunk. It is composed of the acetabulum and femoral head and has important functions such as weight-bearing, connection, stability and movement.

[0003] When problems occur in the hip joint, CT imaging technology is usually used to image the hip joint and analyze the imaging results. However, for patients with metal implants in their bodies (such as metal prostheses after hip replacement surgery), metal artifacts will be generated during CT examinations, interfering with image quality and affecting the observation of surrounding tissues and lesions. Summary of the Invention

[0004] Based on this, an embodiment of the present invention provides a hip joint imaging method and apparatus, which aims to reduce metal artifacts in CT images when a metal implant is present at the hip joint.

[0005] A first aspect of an embodiment of the present invention provides a method for imaging a hip joint, the method comprising:

[0006] Obtaining a three-dimensional model of the hip joint and original CT images layer by layer in the Z-axis direction, and determining the relative position of the metal implant in the hip joint based on the three-dimensional model;

[0007] Determining, based on the relative position, a first CT original image corresponding to the maximum cross-section of the metal implant in the Z-axis direction;

[0008] obtaining, based on the three-dimensional model, an actual contour of the metal implant when it has a maximum cross-section in the Z-axis direction, and determining a display contour of the metal implant in the first CT original image;

[0009] determining influence line segments in different directions around the metal implant, and determining, based on the actual contour and the displayed contour, the influence range of the metal implant on the first CT original image in different directions;

[0010] The first CT original image is optimized according to the influence range and the influence line segment to reduce artifacts.

[0011] Furthermore, after the step of optimizing the first CT original image according to the influence range and the influence line segment to reduce artifacts, the following steps are performed:

[0012] Obtaining the Z-axis position of the first CT original image, and obtaining a preset number of second CT original images on both sides of the Z-axis position according to the Z-axis position;

[0013] performing artifact removal processing on the second CT original images, wherein, during the artifact removal process, obtaining the influence range of the metal implant in different directions in each of the second CT original images;

[0014] According to the change of the influence range, the target influence range of the subsequent CT original image that needs to be processed for artifacts is predicted, and when the influence line segment is confirmed, the analysis is performed within the target influence range.

[0015] Furthermore, the step of determining the influence line segments in different directions around the metal implant includes:

[0016] smoothing the first CT original image using a Gaussian filter to obtain a target CT image, and determining a target display contour of the metal implant in the target CT image;

[0017] According to the target display outline, a preset area surrounding the target display outline is acquired, the gradient direction distribution of all pixels in the preset area is counted, and a direction histogram is constructed;

[0018] Obtaining each histogram peak in the directional histogram, and determining whether each histogram peak is greater than a first threshold;

[0019] If it is determined that the histogram peak is greater than the threshold, a candidate artifact path region is determined, the candidate artifact path region is traversed through a sliding window, and the variance of the pixel gradient direction in the candidate artifact path region is calculated;

[0020] Determining whether the variance is less than a second threshold;

[0021] If it is determined that the variance is less than the second threshold, the influence line segment is determined according to the variance result.

[0022] Furthermore, the step of determining the influence range of the metal implant on the first CT original image in different directions based on the actual contour and the displayed contour includes:

[0023] overlapping the actual contour and the displayed contour according to the relative positions, and dividing the first CT original image into a plurality of regions;

[0024] An influence line segment in each area is obtained, an endpoint of the influence line segment in each area that is farthest from the display outline is determined, and the endpoints are connected to obtain an influence range.

[0025] Furthermore, the step of predicting the target impact range of the subsequent CT original image that needs to be processed for artifacts based on the change of the impact range includes:

[0026] Controlling the actual contour to be proportionally enlarged until the enlarged actual contour is inscribed in the displayed contour, and determining the number of pixels of a preset pixel value in each area, and the maximum distance between the enlarged actual contour and the displayed contour in each area;

[0027] A fitting curve is established for the number of pixels in each area, the maximum distance between the actual outline after magnification in each area and the displayed outline, and the influence range in each area. The fitting curve is used to predict the corresponding target influence range based on the number of pixels in the area and the maximum distance between the actual outline after magnification in the area and the displayed outline.

[0028] Furthermore, the step of dividing the first CT original image into a plurality of regions includes:

[0029] According to the distribution of adjacent influence line segments, influence line segments whose correlations meet preset requirements are regarded as influence line segments of the same region, so as to complete the region division of the first CT original image.

[0030] Furthermore, the step of considering the influence line segments whose correlations meet preset requirements as influence line segments in the same area according to the distribution of adjacent influence line segments includes:

[0031] Obtain the angle formed between adjacent line segments, perform DBSCAN clustering on the angle, and obtain a clustering result;

[0032] Performing partitioning according to the clustering results and determining whether the number of partitioned areas reaches a preset number;

[0033] If it is determined that the number of divided regions does not reach the preset number, the divided regions are evenly divided to obtain all the regions.

[0034] A second aspect of the embodiments of the present invention provides a hip joint imaging system for implementing the hip joint imaging method provided in the first aspect of the embodiments of the present invention, the system comprising:

[0035] The first acquisition module is used to obtain a three-dimensional model of the hip joint and the original CT images layer by layer in the Z-axis direction, and determine the relative position of the metal implant in the hip joint according to the three-dimensional model;

[0036] a first determining module, configured to determine, based on the relative position, a first CT original image corresponding to a maximum cross-section of the metal implant in the Z-axis direction;

[0037] a second acquisition module, configured to acquire, based on the three-dimensional model, an actual contour of the metal implant when it has a maximum cross-section in the Z-axis direction, and simultaneously determine a displayed contour of the metal implant in the first original CT image;

[0038] a second determining module, configured to determine influence line segments in different directions surrounding the metal implant, and determine the influence range of the metal implant on the first CT original image in different directions based on the actual contour and the displayed contour;

[0039] An optimization module is used to optimize the first CT original image according to the influence range and the influence line segment to reduce artifacts.

[0040] A third aspect of an embodiment of the present invention provides a computer-readable storage medium, including:

[0041] The readable storage medium stores one or more programs, which, when executed by a processor, implement the hip joint imaging method as described in the first aspect.

[0042] A fourth aspect of an embodiment of the present invention provides an electronic device, comprising a memory and a processor, wherein:

[0043] The memory is used to store computer programs;

[0044] When the processor is used to execute the computer program stored in the memory, it implements the hip joint imaging method as described in the first aspect.

[0045] A hip joint imaging method and system provided in an embodiment of the present invention obtains a three-dimensional model of the hip joint area and layer-by-layer CT original images in the Z-axis direction, and determines the relative position of a metal implant in the hip joint area based on the three-dimensional model; determines a first CT original image corresponding to the metal implant having a maximum cross-section in the Z-axis direction based on the relative position; obtains the actual contour of the metal implant when it has the maximum cross-section in the Z-axis direction based on the three-dimensional model, and simultaneously determines the displayed contour of the metal implant in the first CT original image; determines the influence line segments in different directions surrounding the metal implant, and determines the influence range of the metal implant on the first CT original image in different directions based on the actual contour and the displayed contour; and optimizes the first CT original image based on the influence range and the influence line segments to reduce artifacts. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A flowchart of a hip joint imaging method according to the first embodiment of the present invention;

[0047] Figure 2 A flowchart of a hip joint imaging method according to a second embodiment of the present invention;

[0048] Figure 3 This is a structural block diagram of a hip joint imaging method system provided in Example 3 of the present invention;

[0049] Figure 4 This is a structural block diagram of an electronic device provided in Example 4 of the present invention. DETAILED DESCRIPTION

[0050] To facilitate understanding of the present invention, the present invention will be described more fully below with reference to the accompanying drawings. The drawings illustrate several embodiments of the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the present invention.

[0051] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be an intermediate element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0053] Example 1

[0054] The first embodiment of the present invention provides a hip joint imaging method, which is applied to a hip joint CT image that produces metal artifacts, wherein the metal artifacts are mainly ray-shaped artifacts generated around metal implants. Figure 1 , is a flowchart for implementing a hip joint imaging method, specifically including steps S01 to S05.

[0055] Step S01: Acquire a three-dimensional model of the hip joint and original CT images layer by layer in the Z-axis direction, and determine the relative position of the metal implant in the hip joint based on the three-dimensional model.

[0056] Specifically, the three-dimensional model of the hip joint can be established by traditional methods, for example, by collecting data through CT / MRI, and then importing the DICOM data into 3D Slicer to generate a three-dimensional model. It can be understood that based on the known three-dimensional model, the relative position of the metal implant in the hip joint can be determined.

[0057] Step S02: determining, based on the relative position, a first CT original image corresponding to the largest cross section of the metal implant in the Z-axis direction.

[0058] By analyzing each original CT image in the Z-axis direction, the first original CT image corresponding to the metal implant with the largest cross-section is found. Because the degree of artifacts in CT images may vary depending on the size of the metal object, the first original CT image corresponding to the metal implant with the largest cross-section is more significantly affected by artifacts.

[0059] Step S03: acquiring the actual contour of the metal implant when it has the maximum cross section in the Z-axis direction according to the three-dimensional model, and determining the displayed contour of the metal implant in the first original CT image.

[0060] Specifically, the actual contour is the outer contour of the actual metal implant, and the displayed contour is the outer contour representing the metal implant displayed in the first CT original image. Usually, the displayed contour surrounds the actual contour, that is, the displayed contour is larger than the actual contour, and the shape of the displayed contour is changed compared to the actual contour.

[0061] Step S04: determining the influence line segments in different directions around the metal implant, and determining the influence range of the metal implant on the first CT original image in different directions according to the actual contour and the displayed contour.

[0062] In this embodiment, to determine the influencing line segments in different directions surrounding the metal implant, that is, to find the ray-shaped artifacts, a Gaussian filter is used to smooth the first CT original image to reduce noise interference and obtain a target CT image. The smoothing process is performed by weighted averaging pixel neighborhood values, and the target display contour of the metal implant is determined in the target CT image.

[0063] According to the target display outline, a preset area around the target display outline is obtained. The preset area can be a valid area in the target CT image excluding the target display outline, which can be manually identified. The gradient direction distribution of all pixels in the preset area is counted, and a direction histogram is constructed. It should be noted that the Sobel operator is used to calculate the gradient. Specifically, the Sobel operator is used to perform convolution operations in the horizontal (x direction) and vertical (y direction) directions to obtain the gradient component g of each pixel. x and g y , and then calculate the gradient amplitude, the formula is:

[0064]

[0065] And calculate the direction, the formula is:

[0066]

[0067] The angle range is mapped to 0° to 180° or 0° to 360°;

[0068] Obtaining each histogram peak in the directional histogram and determining whether each histogram peak is greater than a first threshold. It is understandable that if the pixel ratio in a certain angle interval is significantly higher than that in other directions, it is determined to be a candidate region for an artifact path;

[0069] If it is determined that the histogram peak is greater than the threshold, a candidate artifact path region is determined, the candidate artifact path region is traversed through a sliding window, and the variance of the pixel gradient direction in the candidate artifact path region is calculated;

[0070] Determining whether the variance is less than a second threshold, where a smaller variance indicates a more consistent direction;

[0071] If it is determined that the variance is less than the second threshold, the influence line segment is determined according to the variance result.

[0072] Furthermore, in order to determine the influence range of the metal implant on the first CT original image in different directions, specifically, based on the relative position, the actual contour and the displayed contour are overlapped, and the first CT original image is divided into a plurality of regions. It should be noted that, based on the distribution of adjacent influencing line segments, influencing line segments whose correlation meets preset requirements are considered influencing line segments of the same region to complete the regional division of the first CT original image. The angle formed between adjacent line segments is obtained, and the angle is subjected to DBSCAN clustering to obtain a clustering result. The advantage of using DBSCAN clustering is that the number of cluster centers does not need to be specified.

[0073] Performing partitioning according to the clustering results and determining whether the number of partitioned areas reaches a preset number;

[0074] If it is determined that the number of divided areas does not reach the preset number, the divided areas are evenly divided to obtain all the areas;

[0075] Obtain the influence line segments in each area, determine the endpoints of the influence line segments in each area that are farthest from the display outline, and connect the endpoints to obtain the influence range. It can be understood that the lines between the endpoints are eventually connected to the boundaries of each area to form the influence range.

[0076] Step S05 : optimizing the first CT original image according to the influence range and the influence line segment to reduce artifacts.

[0077] Specifically, pixels of each influencing line segment are replaced within the influencing range to optimize the first CT original image. It should be noted that, taking a certain influencing line segment as an example, the artifact pixel on the influencing line segment is first determined as the center, and the weights of non-artifact pixels in a 5×5 neighborhood are calculated:

[0078]

[0079] Among them, W d (i, j) represents the spatial distance weight of the non-artifact pixel (i, j) in the neighborhood, (a, b) represents the coordinates of the artifact pixel, and ∈ represents a parameter to prevent the denominator from being zero;

[0080] The Sobel operator is introduced to calculate the gradient direction of the neighborhood pixels:

[0081] W g (i,j)=cos(θ (i,j) -θ (a,b) )

[0082] W g (i, j) represents the gradient direction consistency weight of the non-artifact pixel (i, j) in the neighborhood;

[0083] The comprehensive weight of the non-artifact pixel (i, j) in the neighborhood is expressed as:

[0084]

[0085] Finally, fill the artifact pixels on the affected line segment. The formula is expressed as:

[0086] I corrected (a,b)=∑ (i,j)∈Ω W (i,j) I(i,j)

[0087] I corrected (a, b) represents the result after correction of the artifact pixel (a, b).

[0088] In summary, an embodiment of the present invention proposes a hip joint imaging method, which obtains a three-dimensional model of the hip joint area and layer-by-layer CT original images in the Z-axis direction, and determines the relative position of a metal implant at the hip joint area based on the three-dimensional model; determines the first CT original image corresponding to the metal implant having the maximum cross-section in the Z-axis direction based on the relative position; obtains the actual contour of the metal implant when it has the maximum cross-section in the Z-axis direction based on the three-dimensional model, and simultaneously determines the display contour of the metal implant in the first CT original image; determines the influence line segments in different directions around the metal implant, and determines the influence range of the metal implant on the first CT original image in different directions based on the actual contour and the displayed contour; optimizes the first CT original image based on the influence range and the influence line segments to reduce artifacts.

[0089] Example 2

[0090] The second embodiment of the present invention also provides a hip joint imaging method, please refer to Figure 2 , is a flowchart of an implementation method of a hip joint imaging method. This method differs from the first embodiment in that, after the step of optimizing the first CT original image to reduce artifacts based on the influence range and the influence line segment, the method includes:

[0091] Step S11 , obtaining the Z-axis position of the first CT original image, and obtaining a preset number of second CT original images on both sides of the Z-axis position according to the Z-axis position.

[0092] Step S12: performing artifact removal processing on the second CT original images. During the artifact removal process, the influence range of the metal implant in different directions in each of the second CT original images is obtained.

[0093] It should be noted that the method in the first embodiment of the present invention is also used to perform artifact removal processing on the second CT original images. However, during the processing, the influence range of the metal implant in different directions in each second CT original image is recorded.

[0094] Step S13 , predicting the target influence range of the subsequent CT original image that needs to be processed for artifacts based on the change of the influence range, and performing analysis within the target influence range when confirming the influence line segment.

[0095] Specifically, before predicting the target impact range, the actual contour is controlled to be proportionally enlarged until the enlarged actual contour is inscribed in the displayed contour, that is, the actual contour still surrounds the displayed contour, but the displayed contour and the actual contour are partially in contact, and the number of pixels with a preset pixel value in each area and the maximum distance between the enlarged actual contour and the displayed contour in each area are determined;

[0096] Establish a fitting curve of the number of pixels in each area, the farthest distance between the actual outline after magnification in each area and the displayed outline, and the influence range in each area, wherein the fitting curve can use a two-variable linear equation, and the fitting curve is used to predict the corresponding target influence range based on the number of pixels in the area and the farthest distance between the actual outline after magnification in the area and the displayed outline.

[0097] Example 3

[0098] The third embodiment of the present invention provides a hip joint imaging system 200, see Figure 3 , is a structural block diagram of a hip joint imaging method system, the hip joint imaging system 200 includes:

[0099] A first acquisition module 21 is configured to acquire a three-dimensional model of the hip joint and layer-by-layer CT original images in the Z-axis direction, and determine the relative position of the metal implant in the hip joint based on the three-dimensional model;

[0100] A first determining module 22 is configured to determine, based on the relative position, a first CT original image corresponding to the maximum cross-section of the metal implant in the Z-axis direction;

[0101] a second acquisition module 23 for acquiring, based on the three-dimensional model, an actual contour of the metal implant when it has a maximum cross-section in the Z-axis direction, and determining a display contour of the metal implant in the first original CT image;

[0102] A second determining module 24 is configured to determine the influence line segments in different directions around the metal implant, and determine the influence range of the metal implant on the first CT original image in different directions based on the actual contour and the displayed contour;

[0103] The optimization module 25 is configured to optimize the first CT original image according to the influence range and the influence line segment to reduce artifacts.

[0104] Furthermore, in some other embodiments of the present invention, the hip joint imaging system 200 further includes:

[0105] a third acquisition module, configured to acquire a Z-axis position of the first CT original image, and acquire a preset number of second CT original images on both sides of the Z-axis position according to the Z-axis position;

[0106] an artifact processing module, configured to perform artifact removal processing on the second CT original images, wherein, during the artifact processing, an influence range of the metal implant in different directions in each of the second CT original images is obtained;

[0107] A prediction module is configured to predict a target influence range of a subsequent CT original image requiring artifact processing based on changes in the influence range, and when confirming an influence line segment, analyze within the target influence range. The step of predicting the target influence range of a subsequent CT original image requiring artifact processing based on changes in the influence range includes:

[0108] Controlling the actual contour to be proportionally enlarged until the enlarged actual contour is inscribed in the displayed contour, and determining the number of pixels of a preset pixel value in each area, and the maximum distance between the enlarged actual contour and the displayed contour in each area;

[0109] A fitting curve is established for the number of pixels in each area, the maximum distance between the actual outline after magnification in each area and the displayed outline, and the influence range in each area. The fitting curve is used to predict the corresponding target influence range based on the number of pixels in the area and the maximum distance between the actual outline after magnification in the area and the displayed outline.

[0110] Furthermore, in some other embodiments of the present invention, the second determining module 24 includes:

[0111] a smoothing processing unit, configured to smooth the first CT original image using a Gaussian filter to obtain a target CT image, and determine a target display contour of the metal implant in the target CT image;

[0112] a statistical unit, configured to obtain a preset area surrounding the target display outline according to the target display outline, calculate the gradient direction distribution of all pixels in the preset area, and construct a direction histogram;

[0113] a first judging unit, configured to obtain each histogram peak value in the directional histogram and judge whether each histogram peak value is greater than a first threshold value;

[0114] a calculation unit, configured to determine an artifact path candidate region if it is determined that the histogram peak is greater than a threshold, traverse the artifact path candidate region through a sliding window, and calculate the variance of the pixel gradient direction in the artifact path candidate region;

[0115] A second judging unit, configured to judge whether the variance is less than a second threshold;

[0116] The first determining unit is configured to determine the influence line segment according to a variance result if it is determined that the variance is less than a second threshold.

[0117] Furthermore, in some other embodiments of the present invention, the second determining module 24 further includes:

[0118] a dividing unit, configured to overlap the actual contour and the displayed contour according to the relative positions, and divide the first CT original image into a plurality of regions;

[0119] The connecting unit is used to obtain the influence line segments in each area, determine the endpoints of the influence line segments in each area that are farthest from the display outline, and connect the endpoints to obtain the influence range.

[0120] Furthermore, in some other embodiments of the present invention, the dividing unit includes:

[0121] a partitioning subunit, configured to, based on the distribution of adjacent influencing line segments, deem influencing line segments whose correlations meet preset requirements as influencing line segments of the same region, thereby completing the regional partitioning of the first CT original image; specifically, obtaining the angle formed between adjacent line segments, and performing DBSCAN clustering on the angle to obtain a clustering result;

[0122] Performing partitioning according to the clustering results and determining whether the number of partitioned areas reaches a preset number;

[0123] If it is determined that the number of divided regions does not reach the preset number, the divided regions are evenly divided to obtain all the regions.

[0124] Example 4

[0125] The fourth embodiment of the present invention provides an electronic device, see Figure 4 , is a structural block diagram of an electronic device, including a memory 20, a processor 10, and a computer program 30 stored in the memory and executable on the processor. When the processor 10 executes the computer program 30, the imaging method of the hip joint as described above is implemented.

[0126] In some embodiments, the processor 10 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor or other data processing chip, used to run the program code stored in the memory 20 or process data, such as executing access restriction programs.

[0127] Among them, the memory 20 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 20 can be an internal storage unit of an electronic device, such as a hard disk of the electronic device. In other embodiments, the memory 20 can also be an external storage device of an electronic device, such as a plug-in hard disk equipped on the electronic device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Furthermore, the memory 20 can also include both an internal storage unit of the electronic device and an external storage device. The memory 20 can be used not only to store application software and various types of data of the electronic device, but also to temporarily store data that has been output or is to be output.

[0128] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned hip joint imaging method when executed by a processor.

[0129] Those skilled in the art will appreciate that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0130] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0131] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement the hardware: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0132] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0133] The above embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A hip joint imaging method, characterized in that: The method comprises: Obtaining a three-dimensional model of the hip joint and original CT images layer by layer in the Z-axis direction, and determining the relative position of the metal implant in the hip joint based on the three-dimensional model; Determining, based on the relative position, a first CT original image corresponding to the maximum cross-section of the metal implant in the Z-axis direction; obtaining, based on the three-dimensional model, an actual contour of the metal implant when it has a maximum cross-section in the Z-axis direction, and determining a display contour of the metal implant in the first CT original image; determining influence line segments in different directions around the metal implant, and determining, based on the actual contour and the displayed contour, the influence range of the metal implant on the first CT original image in different directions; The first CT original image is optimized according to the influence range and the influence line segment to reduce artifacts.

2. The hip joint imaging method according to claim 1, characterized in that: The step of optimizing the first CT original image according to the influence range and the influence line segment to reduce artifacts includes: Obtaining the Z-axis position of the first CT original image, and obtaining a preset number of second CT original images on both sides of the Z-axis position according to the Z-axis position; performing artifact removal processing on the second CT original images, wherein, during the artifact removal process, obtaining the influence range of the metal implant in different directions in each of the second CT original images; According to the change of the influence range, the target influence range of the subsequent CT original image that needs to be processed for artifacts is predicted, and when the influence line segment is confirmed, the analysis is performed within the target influence range.

3. The hip joint imaging method according to claim 2, characterized in that: The step of determining influence line segments in different directions around the metal implant comprises: smoothing the first CT original image using a Gaussian filter to obtain a target CT image, and determining a target display contour of the metal implant in the target CT image; According to the target display outline, a preset area surrounding the target display outline is acquired, the gradient direction distribution of all pixels in the preset area is counted, and a direction histogram is constructed; Obtaining each histogram peak in the directional histogram, and determining whether each histogram peak is greater than a first threshold; If it is determined that the histogram peak is greater than the threshold, a candidate artifact path region is determined, the candidate artifact path region is traversed through a sliding window, and the variance of the pixel gradient direction in the candidate artifact path region is calculated; Determining whether the variance is less than a second threshold; If it is determined that the variance is less than the second threshold, the influence line segment is determined according to the variance result.

4. The hip joint imaging method according to claim 3, characterized in that: The step of determining the influence range of the metal implant on the first CT original image in different directions according to the actual contour and the displayed contour comprises: overlapping the actual contour and the displayed contour according to the relative positions, and dividing the first CT original image into a plurality of regions; An influence line segment in each area is obtained, an endpoint of the influence line segment in each area that is farthest from the display outline is determined, and the endpoints are connected to obtain an influence range.

5. The hip joint imaging method according to claim 4, characterized in that: The step of predicting the target impact range of the subsequent CT original image that needs to be processed for artifacts based on the change of the impact range includes: Controlling the actual contour to be proportionally enlarged until the enlarged actual contour is inscribed in the displayed contour, and determining the number of pixels of a preset pixel value in each area, and the maximum distance between the enlarged actual contour and the displayed contour in each area; A fitting curve is established for the number of pixels in each area, the maximum distance between the actual outline after magnification in each area and the displayed outline, and the influence range in each area. The fitting curve is used to predict the corresponding target influence range based on the number of pixels in the area and the maximum distance between the actual outline after magnification in the area and the displayed outline.

6. The hip joint imaging method according to claim 5, characterized in that: The step of dividing the first CT original image into a plurality of regions comprises: According to the distribution of adjacent influence line segments, influence line segments whose correlations meet preset requirements are regarded as influence line segments of the same region, so as to complete the region division of the first CT original image.

7. The hip joint imaging method according to claim 6, characterized in that: The step of considering the influence line segments whose correlations meet preset requirements as influence line segments in the same area according to the distribution of adjacent influence line segments includes: Obtain the angle formed between adjacent line segments, perform DBSCAN clustering on the angle, and obtain a clustering result; Performing partitioning according to the clustering results and determining whether the number of partitioned areas reaches a preset number; If it is determined that the number of divided regions does not reach the preset number, the divided regions are evenly divided to obtain all the regions.

8. A hip joint imaging system, characterized in that: A method for imaging a hip joint according to any one of claims 1 to 7, wherein the system comprises: The first acquisition module is used to obtain a three-dimensional model of the hip joint and the original CT images layer by layer in the Z-axis direction, and determine the relative position of the metal implant in the hip joint according to the three-dimensional model; a first determining module, configured to determine, based on the relative position, a first CT original image corresponding to a maximum cross-section of the metal implant in the Z-axis direction; a second acquisition module, configured to acquire, based on the three-dimensional model, an actual contour of the metal implant when it has a maximum cross-section in the Z-axis direction, and simultaneously determine a displayed contour of the metal implant in the first original CT image; a second determining module, configured to determine influence line segments in different directions surrounding the metal implant, and determine the influence range of the metal implant on the first CT original image in different directions based on the actual contour and the displayed contour; An optimization module is used to optimize the first CT original image according to the influence range and the influence line segment to reduce artifacts.

9. A computer-readable storage medium, characterized in that include: The readable storage medium stores one or more programs, which, when executed by a processor, implement the hip joint imaging method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute the computer program stored in the memory, it implements the hip joint imaging method described in any one of claims 1-7.

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